diff --git a/configs/inpainting/deepfillv1/README_zh-CN.md b/configs/inpainting/deepfillv1/README_zh-CN.md
index f48340be25..5524c705fc 100644
--- a/configs/inpainting/deepfillv1/README_zh-CN.md
+++ b/configs/inpainting/deepfillv1/README_zh-CN.md
@@ -16,3 +16,17 @@
```
+
+
+
+**Places365-Challenge**
+
+| Method | Mask Type | Resolution | Train Iters | Test Set | l1 error | PSNR | SSIM | Download |
+| :--------------------------------------------------------------------------: | :---------: | :--------: | :---------: | :-----------: | :------: | :----: | :---: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [DeepFillv1](/configs/inpainting/deepfillv1/deepfillv1_256x256_8x2_places.py) | square bbox | 256x256 | 3500k | Places365-val | 11.019 | 23.429 | 0.862 | [model](https://download.openmmlab.com/mmediting/inpainting/deepfillv1/deepfillv1_256x256_8x2_places_20200619-c00a0e21.pth) \| [log](https://download.openmmlab.com/mmediting/inpainting/deepfillv1/deepfillv1_256x256_8x2_places_20200619-c00a0e21.log.json) |
+
+**CelebA-HQ**
+
+| Method | Mask Type | Resolution | Train Iters | Test Set | l1 error | PSNR | SSIM | Download |
+| :--------------------------------------------------------------------------: | :---------: | :--------: | :---------: | :--------: | :------: | :----: | :---: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [DeepFillv1](/configs/inpainting/deepfillv1/deepfillv1_256x256_4x4_celeba.py) | square bbox | 256x256 | 1500k | CelebA-val | 6.677 | 26.878 | 0.911 | [model](https://download.openmmlab.com/mmediting/inpainting/deepfillv1/deepfillv1_256x256_4x4_celeba_20200619-dd51a855.pth) \| [log](https://download.openmmlab.com/mmediting/inpainting/deepfillv1/deepfillv1_256x256_4x4_celeba_20200619-dd51a855.log.json) |
diff --git a/configs/inpainting/deepfillv2/README_zh-CN.md b/configs/inpainting/deepfillv2/README_zh-CN.md
index 9714d3e92b..27e3fdfe12 100644
--- a/configs/inpainting/deepfillv2/README_zh-CN.md
+++ b/configs/inpainting/deepfillv2/README_zh-CN.md
@@ -15,3 +15,17 @@
```
+
+
+
+**Places365-Challenge**
+
+| Method | Mask Type | Resolution | Train Iters | Test Set | l1 error | PSNR | SSIM | Download |
+| :--------------------------------------------------------------------------: | :-------: | :--------: | :---------: | :-----------: | :------: | :----: | :---: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [DeepFillv2](/configs/inpainting/deepfillv2/deepfillv2_256x256_8x2_places.py) | free-form | 256x256 | 100k | Places365-val | 8.635 | 22.398 | 0.815 | [model](https://download.openmmlab.com/mmediting/inpainting/deepfillv2/deepfillv2_256x256_8x2_places_20200619-10d15793.pth) \| [log](https://download.openmmlab.com/mmediting/inpainting/deepfillv2/deepfillv2_256x256_8x2_places_20200619-10d15793.log.json) |
+
+**CelebA-HQ**
+
+| Method | Mask Type | Resolution | Train Iters | Test Set | l1 error | PSNR | SSIM | Download |
+| :--------------------------------------------------------------------------: | :-------: | :--------: | :---------: | :--------: | :------: | :----: | :---: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [DeepFillv2](/configs/inpainting/deepfillv2/deepfillv2_256x256_8x2_celeba.py) | free-form | 256x256 | 20k | CelebA-val | 5.411 | 25.721 | 0.871 | [model](https://download.openmmlab.com/mmediting/inpainting/deepfillv2/deepfillv2_256x256_8x2_celeba_20200619-c96e5f12.pth) \| [log](https://download.openmmlab.com/mmediting/inpainting/deepfillv2/deepfillv2_256x256_8x2_celeba_20200619-c96e5f12.log.json) |
diff --git a/configs/inpainting/global_local/README_zh-CN.md b/configs/inpainting/global_local/README_zh-CN.md
index c4461b362d..ea62cdfde4 100644
--- a/configs/inpainting/global_local/README_zh-CN.md
+++ b/configs/inpainting/global_local/README_zh-CN.md
@@ -18,3 +18,19 @@
```
+
+
+
+*Note that we do not apply the post-processing module in Global&Local for a fair comparison with current deep inpainting methods.*
+
+**Places365-Challenge**
+
+| Method | Mask Type | Resolution | Train Iters | Test Set | l1 error | PSNR | SSIM | Download |
+| :-----------------------------------------------------------------------: | :---------: | :--------: | :---------: | :-----------: | :------: | :----: | :---: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [Global&Local](/configs/inpainting/global_local/gl_256x256_8x12_places.py) | square bbox | 256x256 | 500k | Places365-val | 11.164 | 23.152 | 0.862 | [model](https://download.openmmlab.com/mmediting/inpainting/global_local/gl_256x256_8x12_places_20200619-52a040a8.pth) \| [log](https://download.openmmlab.com/mmediting/inpainting/global_local/gl_256x256_8x12_places_20200619-52a040a8.log.json) |
+
+**CelebA-HQ**
+
+| Method | Mask Type | Resolution | Train Iters | Test Set | l1 error | PSNR | SSIM | Download |
+| :-----------------------------------------------------------------------: | :---------: | :--------: | :---------: | :--------: | :------: | :----: | :---: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [Global&Local](/configs/inpainting/global_local/gl_256x256_8x12_celeba.py) | square bbox | 256x256 | 500k | CelebA-val | 6.678 | 26.780 | 0.904 | [model](https://download.openmmlab.com/mmediting/inpainting/global_local/gl_256x256_8x12_celeba_20200619-5af0493f.pth) \| [log](https://download.openmmlab.com/mmediting/inpainting/global_local/gl_256x256_8x12_celeba_20200619-5af0493f.log.json) |
diff --git a/configs/inpainting/partial_conv/README_zh-CN.md b/configs/inpainting/partial_conv/README_zh-CN.md
index a6034fb758..fcc68051b7 100644
--- a/configs/inpainting/partial_conv/README_zh-CN.md
+++ b/configs/inpainting/partial_conv/README_zh-CN.md
@@ -16,3 +16,17 @@
```
+
+
+
+**Places365-Challenge**
+
+| Method | Mask Type | Resolution | Train Iters | Test Set | l1 error | PSNR | SSIM | Download |
+| :-------------------------------------------------------------------------: | :-------: | :--------: | :---------: | :-----------: | :------: | :----: | :---: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [PConv](/configs/inpainting/partial_conv/pconv_256x256_stage2_4x2_places.py) | free-form | 256x256 | 500k | Places365-val | 8.776 | 22.762 | 0.801 | [model](https://download.openmmlab.com/mmediting/inpainting/pconv/pconv_256x256_stage2_4x2_places_20200619-1ffed0e8.pth) \| [log](https://download.openmmlab.com/mmediting/inpainting/pconv/pconv_256x256_stage2_4x2_places_20200619-1ffed0e8.log.json) |
+
+**CelebA-HQ**
+
+| Method | Mask Type | Resolution | Train Iters | Test Set | l1 error | PSNR | SSIM | Download |
+| :-------------------------------------------------------------------------: | :-------: | :--------: | :---------: | :--------: | :------: | :----: | :---: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [PConv](/configs/inpainting/partial_conv/pconv_256x256_stage2_4x2_celeba.py) | free-form | 256x256 | 500k | CelebA-val | 5.990 | 25.404 | 0.853 | [model](https://download.openmmlab.com/mmediting/inpainting/pconv/pconv_256x256_stage2_4x2_celeba_20200619-860f8b95.pth) \| [log](https://download.openmmlab.com/mmediting/inpainting/pconv/pconv_256x256_stage2_4x2_celeba_20200619-860f8b95.log.json) |
diff --git a/configs/mattors/dim/README_zh-CN.md b/configs/mattors/dim/README_zh-CN.md
index 0f8b52eb69..e672b73130 100644
--- a/configs/mattors/dim/README_zh-CN.md
+++ b/configs/mattors/dim/README_zh-CN.md
@@ -15,3 +15,23 @@
```
+
+
+
+| Method | SAD | MSE | GRAD | CONN | Download |
+| :------------------------------------------------------------------------: | :------: | :-------: | :------: | :------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| stage1 (paper) | 54.6 | 0.017 | 36.7 | 55.3 | - |
+| stage3 (paper) | **50.4** | **0.014** | 31.0 | 50.8 | - |
+| [stage1 (our)](/configs/mattors/dim/dim_stage1_v16_1x1_1000k_comp1k.py) | 53.8 | 0.017 | 32.7 | 54.5 | [model](https://download.openmmlab.com/mmediting/mattors/dim/dim_stage1_v16_1x1_1000k_comp1k_SAD-53.8_20200605_140257-979a420f.pth) \| [log](https://download.openmmlab.com/mmediting/mattors/dim/dim_stage1_v16_1x1_1000k_comp1k_20200605_140257.log.json) |
+| [stage2 (our)](/configs/mattors/dim/dim_stage2_v16_pln_1x1_1000k_comp1k.py) | 52.3 | 0.016 | 29.4 | 52.4 | [model](https://download.openmmlab.com/mmediting/mattors/dim/dim_stage2_v16_pln_1x1_1000k_comp1k_SAD-52.3_20200607_171909-d83c4775.pth) \| [log](https://download.openmmlab.com/mmediting/mattors/dim/dim_stage2_v16_pln_1x1_1000k_comp1k_20200607_171909.log.json) |
+| [stage3 (our)](/configs/mattors/dim/dim_stage3_v16_pln_1x1_1000k_comp1k.py) | 50.6 | 0.015 | **29.0** | **50.7** | [model](https://download.openmmlab.com/mmediting/mattors/dim/dim_stage3_v16_pln_1x1_1000k_comp1k_SAD-50.6_20200609_111851-647f24b6.pth) \| [log](https://download.openmmlab.com/mmediting/mattors/dim/dim_stage3_v16_pln_1x1_1000k_comp1k_20200609_111851.log.json) |
+
+**NOTE**
+
+* stage1: train the encoder-decoder part without the refinement part. \
+* stage2: fix the encoder-decoder part and train the refinement part. \
+* stage3: fine-tune the whole network.
+
+> The performance of the model is not stable during the training. Thus, the reported performance is not from the last checkpoint. Instead, it is the best performance of all validations during training.
+
+> The performance of training (best performance) with different random seeds diverges in a large range. You may need to run several experiments for each setting to obtain the above performance.
diff --git a/configs/mattors/gca/README_zh-CN.md b/configs/mattors/gca/README_zh-CN.md
index be55694525..5ed4aac4a4 100644
--- a/configs/mattors/gca/README_zh-CN.md
+++ b/configs/mattors/gca/README_zh-CN.md
@@ -14,3 +14,19 @@
```
+
+
+
+| Method | SAD | MSE | GRAD | CONN | Download |
+| :--------------------------------------------------------------------: | :-------: | :--------: | :-------: | :-------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| baseline (paper) | 40.62 | 0.0106 | 21.53 | 38.43 | - |
+| GCA (paper) | 35.28 | 0.0091 | 16.92 | 32.53 | - |
+| [baseline (our)](/configs/mattors/gca/baseline_r34_4x10_200k_comp1k.py) | 36.50 | 0.0090 | 17.40 | 34.33 | [model](https://download.openmmlab.com/mmediting/mattors/gca/baseline_r34_4x10_200k_comp1k_SAD-36.50_20200614_105701-95be1750.pth) \| [log](https://download.openmmlab.com/mmediting/mattors/gca/baseline_r34_4x10_200k_comp1k_20200614_105701.log.json) |
+| [GCA (our)](/configs/mattors/gca/gca_r34_4x10_200k_comp1k.py) | **34.77** | **0.0080** | **16.33** | **32.20** | [model](https://download.openmmlab.com/mmediting/mattors/gca/gca_r34_4x10_200k_comp1k_SAD-34.77_20200604_213848-4369bea0.pth) \| [log](https://download.openmmlab.com/mmediting/mattors/gca/gca_r34_4x10_200k_comp1k_20200604_213848.log.json) |
+
+**More results**
+
+| Method | SAD | MSE | GRAD | CONN | Download |
+| :-----------------------------------------------------------------------------------------: | :---: | :----: | :---: | :---: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [baseline (with DIM pipeline)](/configs/mattors/gca/baseline_dimaug_r34_4x10_200k_comp1k.py) | 49.95 | 0.0144 | 30.21 | 49.67 | [model](https://download.openmmlab.com/mmediting/mattors/gca/baseline_dimaug_r34_4x10_200k_comp1k_SAD-49.95_20200626_231612-535c9a11.pth) \| [log](https://download.openmmlab.com/mmediting/mattors/gca/baseline_dimaug_r34_4x10_200k_comp1k_20200626_231612.log.json) |
+| [GCA (with DIM pipeline)](/configs/mattors/gca/gca_dimaug_r34_4x10_200k_comp1k.py) | 49.42 | 0.0129 | 28.07 | 49.47 | [model](https://download.openmmlab.com/mmediting/mattors/gca/gca_dimaug_r34_4x10_200k_comp1k_SAD-49.42_20200626_231422-8e9cc127.pth) \| [log](https://download.openmmlab.com/mmediting/mattors/gca/gca_dimaug_r34_4x10_200k_comp1k_20200626_231422.log.json) |
diff --git a/configs/mattors/indexnet/README_zh-CN.md b/configs/mattors/indexnet/README_zh-CN.md
index c6dd761aaa..f2ec3f10b4 100644
--- a/configs/mattors/indexnet/README_zh-CN.md
+++ b/configs/mattors/indexnet/README_zh-CN.md
@@ -14,3 +14,18 @@
```
+
+
+
+| Method | SAD | MSE | GRAD | CONN | Download |
+| :--------------------------------------------------------------------------: | :------: | :-------: | :------: | :------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| M2O DINs (paper) | 45.8 | 0.013 | 25.9 | **43.7** | - |
+| [M2O DINs (our)](/configs/mattors/indexnet/indexnet_mobv2_1x16_78k_comp1k.py) | **45.6** | **0.012** | **25.5** | 44.8 | [model](https://download.openmmlab.com/mmediting/mattors/indexnet/indexnet_mobv2_1x16_78k_comp1k_SAD-45.6_20200618_173817-26dd258d.pth) \| [log](https://download.openmmlab.com/mmediting/mattors/indexnet/indexnet_mobv2_1x16_78k_comp1k_20200618_173817.log.json) |
+
+> The performance of training (best performance) with different random seeds diverges in a large range. You may need to run several experiments for each setting to obtain the above performance.
+
+**More result**
+
+| Method | SAD | MSE | GRAD | CONN | Download |
+| :-----------------------------------------------------------------------------------------------: | :---: | :---: | :---: | :---: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [M2O DINs (with DIM pipeline)](/configs/mattors/indexnet/indexnet_dimaug_mobv2_1x16_78k_comp1k.py) | 50.1 | 0.016 | 30.8 | 49.5 | [model](https://download.openmmlab.com/mmediting/mattors/indexnet/indexnet_dimaug_mobv2_1x16_78k_comp1k_SAD-50.1_20200626_231857-af359436.pth) \| [log](https://download.openmmlab.com/mmediting/mattors/indexnet/indexnet_dimaug_mobv2_1x16_78k_comp1k_20200626_231857.log.json) |
diff --git a/configs/restorers/basicvsr/README_zh-CN.md b/configs/restorers/basicvsr/README_zh-CN.md
index 752660ed6c..4a65bcd0ed 100644
--- a/configs/restorers/basicvsr/README_zh-CN.md
+++ b/configs/restorers/basicvsr/README_zh-CN.md
@@ -15,3 +15,14 @@
```
+
+
+
+Evaluated on RGB channels for REDS4 and Y channel for others. The metrics are `PSNR` / `SSIM` .
+The pretrained weights of SPyNet can be found [here](https://download.openmmlab.com/mmediting/restorers/basicvsr/spynet_20210409-c6c1bd09.pth).
+
+| Method | REDS4 (BIx4)
PSNR/SSIM (RGB) | Vimeo-90K-T (BIx4)
PSNR/SSIM (Y) | Vid4 (BIx4)
PSNR/SSIM (Y) | UDM10 (BDx4)
PSNR/SSIM (Y) | Vimeo-90K-T (BDx4)
PSNR/SSIM (Y) | Vid4 (BDx4)
PSNR/SSIM (Y) | Download |
+|:------------------------------------------------------------------------------------------------------------------------------:|:-------------------------------:|:-----------------------------------:|:----------------------------:|:-----------------------------:|:-----------------------------------:|:----------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| [basicvsr_reds4](https://github.com/open-mmlab/mmediting/blob/master/configs/restorers/basicvsr/basicvsr_reds4.py) | **31.4170/0.8909** | 36.2848/0.9395 | 27.2694/0.8318 | 33.4478/0.9306 | 34.4700/0.9286 | 24.4541/0.7455 | [model](https://download.openmmlab.com/mmediting/restorers/basicvsr/basicvsr_reds4_20120409-0e599677.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/basicvsr/basicvsr_reds4_20210409_092646.log.json) |
+| [basicvsr_vimeo90k_bi](https://github.com/open-mmlab/mmediting/blob/master/configs/restorers/basicvsr/basicvsr_vimeo90k_bi.py) | 30.3128/0.8660 | **37.2026/0.9451** | **27.2755/0.8248** | 34.5554/0.9434 | 34.8097/0.9316 | 25.0517/0.7636 | [model](https://download.openmmlab.com/mmediting/restorers/basicvsr/basicvsr_vimeo90k_bi_20210409-d2d8f760.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/basicvsr/basicvsr_vimeo90k_bi_20210409_132702.log.json) |
+| [basicvsr_vimeo90k_bd](https://github.com/open-mmlab/mmediting/blob/master/configs/restorers/basicvsr/basicvsr_vimeo90k_bd.py) | 29.0376/0.8481 | 34.6427/0.9335 | 26.2708/0.8022 | **39.9953/0.9695** | **37.5501/0.9499** | **27.9791/0.8556** | [model](https://download.openmmlab.com/mmediting/restorers/basicvsr/basicvsr_vimeo90k_bd_20210409-0154dd64.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/basicvsr/basicvsr_vimeo90k_bd_20210409_132740.log.json) |
diff --git a/configs/restorers/dic/README_zh-CN.md b/configs/restorers/dic/README_zh-CN.md
index 51f12558b4..0536e1a33b 100644
--- a/configs/restorers/dic/README_zh-CN.md
+++ b/configs/restorers/dic/README_zh-CN.md
@@ -16,3 +16,15 @@
```
+
+
+
+Evaluated on RGB channels, `scale` pixels in each border are cropped before evaluation.
+The metrics are `PSNR / SSIM` .
+
+In the log data of `dic_gan_x8c48b6_g4_150k_CelebAHQ`, DICGAN is verified on the first 9 pictures of the test set of CelebA-HQ, so `PSNR/SSIM` shown in the follow table is different from the log data.
+
+| Method | scale | CelebA-HQ | Download |
+| :--------------------------------------------------------------------------------------------: | :---: | :--------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [dic_x8c48b6_g4_150k_CelebAHQ](/configs/restorers/dic/dic_x8c48b6_g4_150k_CelebAHQ.py) | x8 | 25.2319 / 0.7422 | [model](https://download.openmmlab.com/mmediting/restorers/dic/dic_x8c48b6_g4_150k_CelebAHQ_20210611-5d3439ca.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/dic/dic_x8c48b6_g4_150k_CelebAHQ_20210611-5d3439ca.log.json) |
+| [dic_gan_x8c48b6_g4_150k_CelebAHQ](/configs/restorers/dic/dic_gan_x8c48b6_g4_500k_CelebAHQ.py) | x8 | 23.6241 / 0.6721 | [model](https://download.openmmlab.com/mmediting/restorers/dic/dic_gan_x8c48b6_g4_500k_CelebAHQ_20210625-3b89a358.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/dic/dic_gan_x8c48b6_g4_500k_CelebAHQ_20210625-3b89a358.log.json) |
diff --git a/configs/restorers/edsr/README_zh-CN.md b/configs/restorers/edsr/README_zh-CN.md
index 79d3b5fdcf..142017f01c 100644
--- a/configs/restorers/edsr/README_zh-CN.md
+++ b/configs/restorers/edsr/README_zh-CN.md
@@ -16,3 +16,14 @@
```
+
+
+
+Evaluated on RGB channels, `scale` pixels in each border are cropped before evaluation.
+The metrics are `PSNR / SSIM` .
+
+| Method | Set5 | Set14 | DIV2K | Download |
+| :------------------------------------------------------------------------------------: | :--------------: | :--------------: | :--------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [edsr_x2c64b16_1x16_300k_div2k](/configs/restorers/edsr/edsr_x2c64b16_g1_300k_div2k.py) | 35.7592 / 0.9372 | 31.4290 / 0.8874 | 34.5896 / 0.9352 | [model](https://download.openmmlab.com/mmediting/restorers/edsr/edsr_x2c64b16_1x16_300k_div2k_20200604-19fe95ea.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/edsr/edsr_x2c64b16_1x16_300k_div2k_20200604_221933.log.json) |
+| [edsr_x3c64b16_1x16_300k_div2k](/configs/restorers/edsr/edsr_x3c64b16_g1_300k_div2k.py) | 32.3301 / 0.8912 | 28.4125 / 0.8022 | 30.9154 / 0.8711 | [model](https://download.openmmlab.com/mmediting/restorers/edsr/edsr_x3c64b16_1x16_300k_div2k_20200608-36d896f4.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/edsr/edsr_x3c64b16_1x16_300k_div2k_20200608_114850.log.json) |
+| [edsr_x4c64b16_1x16_300k_div2k](/configs/restorers/edsr/edsr_x4c64b16_g1_300k_div2k.py) | 30.2223 / 0.8500 | 26.7870 / 0.7366 | 28.9675 / 0.8172 | [model](https://download.openmmlab.com/mmediting/restorers/edsr/edsr_x4c64b16_1x16_300k_div2k_20200608-3c2af8a3.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/edsr/edsr_x4c64b16_1x16_300k_div2k_20200608_115148.log.json) |
diff --git a/configs/restorers/edvr/README_zh-CN.md b/configs/restorers/edvr/README_zh-CN.md
index 7aa3994a17..c4d7886911 100644
--- a/configs/restorers/edvr/README_zh-CN.md
+++ b/configs/restorers/edvr/README_zh-CN.md
@@ -16,3 +16,13 @@
```
+
+
+
+Evaluated on RGB channels.
+The metrics are `PSNR / SSIM` .
+
+| Method | REDS4 | Download |
+| :-----------------------------------------------------------------------------------: | :---------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [edvrm_wotsa_x4_8x4_600k_reds](/configs/restorers/edvr/edvrm_wotsa_x4_g8_600k_reds.py) | 30.3430 / 0.8664 | [model](https://download.openmmlab.com/mmediting/restorers/edvr/edvrm_wotsa_x4_8x4_600k_reds_20200522-0570e567.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/edvr/edvrm_wotsa_x4_8x4_600k_reds_20200522_141644.log.json) |
+| [edvrm_x4_8x4_600k_reds](/configs/restorers/edvr/edvrm_x4_g8_600k_reds.py) | 30.4194 / 0.8684 | [model](https://download.openmmlab.com/mmediting/restorers/edvr/edvrm_x4_8x4_600k_reds_20210625-e29b71b5.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/edvr/edvrm_x4_8x4_600k_reds_20200622_102544.log.json) |
diff --git a/configs/restorers/esrgan/README_zh-CN.md b/configs/restorers/esrgan/README_zh-CN.md
index 3d9ccd07f1..7617377e48 100644
--- a/configs/restorers/esrgan/README_zh-CN.md
+++ b/configs/restorers/esrgan/README_zh-CN.md
@@ -16,3 +16,13 @@
```
+
+
+
+Evaluated on RGB channels, `scale` pixels in each border are cropped before evaluation.
+The metrics are `PSNR / SSIM` .
+
+| Method | Set5 | Set14 | DIV2K | Download |
+| :------------------------------------------------------------------------------------------------------------: | :---------------: | :--------------: | :--------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [esrgan_psnr_x4c64b23g32_1x16_1000k_div2k](/configs/restorers/esrgan/esrgan_psnr_x4c64b23g32_g1_1000k_div2k.py) | 30.6428 / 0.8559 | 27.0543 / 0.7447 | 29.3354 / 0.8263 | [model](https://download.openmmlab.com/mmediting/restorers/esrgan/esrgan_psnr_x4c64b23g32_1x16_1000k_div2k_20200420-bf5c993c.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/esrgan/esrgan_psnr_x4c64b23g32_1x16_1000k_div2k_20200420_112550.log.json) |
+| [esrgan_x4c64b23g32_1x16_400k_div2k](/configs/restorers/esrgan/esrgan_x4c64b23g32_g1_400k_div2k.py) | 28.2700 / 0.7778 | 24.6328 / 0.6491 | 26.6531 / 0.7340 | [model](https://download.openmmlab.com/mmediting/restorers/esrgan/esrgan_x4c64b23g32_1x16_400k_div2k_20200508-f8ccaf3b.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/esrgan/esrgan_x4c64b23g32_1x16_400k_div2k_20200508_191042.log.json) |
diff --git a/configs/restorers/glean/README_zh-CN.md b/configs/restorers/glean/README_zh-CN.md
index 1fa7eca521..8b67e83a05 100644
--- a/configs/restorers/glean/README_zh-CN.md
+++ b/configs/restorers/glean/README_zh-CN.md
@@ -14,3 +14,13 @@
```
+
+
+
+For the meta info used in training and test, please refer to [here](https://github.com/ckkelvinchan/GLEAN). The results are evaluated on RGB channels.
+
+| Method | PSNR | Download |
+|:---------------------------------------------------------------------------------------------------------------:|:-----:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| [glean_cat_8x](/configs/restorers/glean/glean_cat_8x.py) | 23.98 | [model](https://download.openmmlab.com/mmediting/restorers/glean/glean_cat_8x_20210614-d3ac8683.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/glean/glean_cat_8x_20210614_145540.log.json) |
+| [glean_ffhq_16x](/configs/restorers/glean/glean_ffhq_16x.py) | 26.91 | [model](https://download.openmmlab.com/mmediting/restorers/glean/glean_ffhq_16x_20210527-61a3afad.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/glean/glean_ffhq_16x_20210527_194536.log.json) |
+| [glean_cat_16x](/configs/restorers/glean/glean_cat_16x.py) | 20.88 | [model](https://download.openmmlab.com/mmediting/restorers/glean/glean_cat_16x_20210527-68912543.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/glean/glean_cat_16x_20210527_103708.log.json) |
diff --git a/configs/restorers/iconvsr/README_zh-CN.md b/configs/restorers/iconvsr/README_zh-CN.md
index e054b10916..9fdfefcb25 100644
--- a/configs/restorers/iconvsr/README_zh-CN.md
+++ b/configs/restorers/iconvsr/README_zh-CN.md
@@ -15,3 +15,14 @@
```
+
+
+
+Evaluated on RGB channels for REDS4 and Y channel for others. The metrics are `PSNR` / `SSIM` .
+The pretrained weights of the IconVSR components can be found here: [SPyNet](https://download.openmmlab.com/mmediting/restorers/basicvsr/spynet_20210409-c6c1bd09.pth), [EDVR-M for REDS](https://download.openmmlab.com/mmediting/restorers/iconvsr/edvrm_reds_20210413-3867262f.pth), and [EDVR-M for Vimeo-90K](https://download.openmmlab.com/mmediting/restorers/iconvsr/edvrm_vimeo90k_20210413-e40e99a8.pth).
+
+| Method | REDS4 (BIx4)
PSNR/SSIM (RGB) | Vimeo-90K-T (BIx4)
PSNR/SSIM (Y) | Vid4 (BIx4)
PSNR/SSIM (Y) | UDM10 (BDx4)
PSNR/SSIM (Y) | Vimeo-90K-T (BDx4)
PSNR/SSIM (Y) | Vid4 (BDx4)
PSNR/SSIM (Y) | Download |
+|:---------------------------------------------------------------------------------------------------------------------------:|:-------------------------------:|:-----------------------------------:|:----------------------------:|:-----------------------------:|:-----------------------------------:|:----------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| [iconvsr_reds4](https://github.com/open-mmlab/mmediting/blob/master/configs/restorers/iconvsr/iconvsr_reds.py) | **31.6926/0.8951** | 36.4983/0.9416 | **27.4809/0.8354** | 35.3377/0.9471 | 34.4299/0.9287 | 25.2110/0.7732 | [model](https://download.openmmlab.com/mmediting/restorers/iconvsr/iconvsr_reds4_20210413-9e09d621.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/iconvsr/iconvsr_reds4_20210413_222735.log.json) |
+| [iconvsr_vimeo90k_bi](https://github.com/open-mmlab/mmediting/blob/master/configs/restorers/iconvsr/iconvsr_vimeo90k_bi.py) | 30.3452/0.8659 | **37.3729/0.9467** | 27.4238/0.8297 | 34.2595/0.9398 | 34.5548/0.9295 | 24.6666/0.7491 | [model](https://download.openmmlab.com/mmediting/restorers/iconvsr/iconvsr_vimeo90k_bi_20210413-7c7418dc.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/iconvsr/iconvsr_vimeo90k_bi_20210413_222757.log.json) |
+| [iconvsr_vimeo90k_bd](https://github.com/open-mmlab/mmediting/blob/master/configs/restorers/iconvsr/iconvsr_vimeo90k_bd.py) | 29.0150/0.8465 | 34.6780/0.9339 | 26.3109/0.8028 | **40.0640/0.9697** | **37.7573/0.9517** | **28.2464/0.8612** | [model](https://download.openmmlab.com/mmediting/restorers/iconvsr/iconvsr_vimeo90k_bd_20210414-5f38cb34.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/iconvsr/iconvsr_vimeo90k_bd_20210414_084128.log.json) |
diff --git a/configs/restorers/liif/README_zh-CN.md b/configs/restorers/liif/README_zh-CN.md
index f8d61e9dd5..e983ba12ad 100644
--- a/configs/restorers/liif/README_zh-CN.md
+++ b/configs/restorers/liif/README_zh-CN.md
@@ -16,3 +16,25 @@
```
+
+
+
+| method | scale | Set5
PSNR / SSIM | Set14
PSNR / SSIM | DIV2K
PSNR / SSIM | Download |
+| :--------------------------------------------------------------------------------------------------------------: | :---: | :-----------------: | :------------------: | :-------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [liif_edsr_norm_x2-4_c64b16_g1_1000k_div2k](/configs/restorers/liif/liif_edsr_norm_x2-4_c64b16_g1_1000k_div2k.py) | x2 | 35.7148 / 0.9367 | 31.5936 / 0.8889 | 34.5896 / 0.9352 | [model](https://download.openmmlab.com/mmediting/restorers/liif/liif_edsr_norm_c64b16_g1_1000k_div2k_20210319-329ce255.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/liif/liif_edsr_norm_c64b16_g1_1000k_div2k_20210319-329ce255.log.json) |
+| △ | x3 | 32.3596 / 0.8914 | 28.4475 / 0.8040 | 30.9154 / 0.8720 | △ |
+| △ | x4 | 30.2583 / 0.8513 | 26.7867 / 0.7377 | 29.0048 / 0.8183 | △ |
+| [liif_edsr_norm_c64b16_g1_1000k_div2k](/configs/restorers/liif/liif_edsr_norm_c64b16_g1_1000k_div2k.py) | x2 | 35.7120 / 0.9365 | 31.6106 / 0.8891 | 34.6401 / 0.9353 | [model](https://download.openmmlab.com/mmediting/restorers/liif/liif_edsr_norm_c64b16_g1_1000k_div2k_20210319-329ce255.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/liif/liif_edsr_norm_c64b16_g1_1000k_div2k_20210319-329ce255.log.json) |
+| △ | x3 | 32.3655 / 0.8913 | 28.4605 / 0.8039 | 30.9597 / 0.8711 | △ |
+| △ | x4 | 30.2668 / 0.8511 | 26.8093 / 0.7377 | 29.0059 / 0.8183 | △ |
+| △ | x6 | 27.0907 / 0.7775 | 24.7129 / 0.6438 | 26.7694 / 0.7422 | △ |
+| △ | x12 | 22.9046 / 0.6255 | 21.5378 / 0.5088 | 23.7269 / 0.6373 | △ |
+| △ | x18 | 20.8445 / 0.5390 | 20.0215 / 0.4521 | 22.1920 / 0.5947 | △ |
+| △ | x24 | 19.7305 / 0.5033 | 19.0703 / 0.4218 | 21.2025 / 0.5714 | △ |
+| △ | x30 | 18.6646 / 0.4818 | 18.0210 / 0.3905 | 20.5022 / 0.5568 | △ |
+
+Note:
+* △ refers to ditto.
+* The two configs only differs in _testing pipeline_. So they use the same checkpoint.
+* Data is normalized according to [EDSR](/configs/restorers/edsr).
+* Evaluated on RGB channels, `scale` pixels in each border are cropped before evaluation.
diff --git a/configs/restorers/rdn/README_zh-CN.md b/configs/restorers/rdn/README_zh-CN.md
index 3d34de7b12..a9bd6fe72e 100644
--- a/configs/restorers/rdn/README_zh-CN.md
+++ b/configs/restorers/rdn/README_zh-CN.md
@@ -15,3 +15,14 @@
```
+
+
+
+Evaluated on RGB channels, `scale` pixels in each border are cropped before evaluation.
+The metrics are `PSNR / SSIM` .
+
+| Method | Set5 | Set14 | DIV2K | Download |
+| :------------------------------------------------------------------------------------: | :--------------: | :--------------: | :--------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [rdn_x2c64b16_g1_1000k_div2k](/configs/restorers/rdn/rdn_x2c64b16_g1_1000k_div2k.py) | 35.9883 / 0.9385 | 31.8366 / 0.8920 | 34.9392 / 0.9380 | [model](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x2c64b16_g1_1000k_div2k_20210419-dc146009.pth?versionId=CAEQJxiBgMC774LGyBciIGU3ZGRkZWM3Y2Y0ZjQ2OTliZTc2NmM5ZWY0MDA1MDU3) \| [log](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x2c64b16_g1_1000k_div2k_20210419-dc146009.log.json?versionId=CAEQJxiBgICf04_HyBciIDFkMzBiY2Y2ZDE2ZDQ0ZWE4M2MxMjMwMzdhMzY1ZTUz) |
+| [rdn_x3c64b16_g1_1000k_div2k](/configs/restorers/rdn/rdn_x3c64b16_g1_1000k_div2k.py) | 32.6051 / 0.8943 | 28.6338 / 0.8077 | 31.2153 / 0.8763 | [model](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x3c64b16_g1_1000k_div2k_20210419-b93cb6aa.pth?versionId=CAEQJxiBgMC3v9LFyBciIGExYWY0NTI0YWVkODQxZDRiYWNlYjViY2E5MzQ4OTc1) \| [log](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x3c64b16_g1_1000k_div2k_20210419-b93cb6aa.log.json?versionId=CAEQJxiBgMCtwtLFyBciIDNmNzZjNTUyYTk0MjQ2OTBiYjJiNDNjMTI0NGZhYmI4) |
+| [rdn_x4c64b16_g1_1000k_div2k](/configs/restorers/rdn/rdn_x4c64b16_g1_1000k_div2k.py) | 30.4922 / 0.8548 | 26.9570 / 0.7423 | 29.1925 / 0.8233 | [model](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x4c64b16_g1_1000k_div2k_20210419-3577d44f.pth?versionId=CAEQJxiBgICwxdLFyBciIGFlMzVhNTBlOGEyNDQwMGI5OGJjOTJkMDQ1ZDJjOTM2) \| [log](https://download.openmmlab.com/mmediting/restorers/rdn/rdn_x4c64b16_g1_1000k_div2k_20210419-3577d44f.log.json?versionId=CAEQJxiBgIC9xtLFyBciIGQ5YTJhMjY0OTE1YjRiMTQ5OTc5YzQ2MjM4ZGVkZWQ1) |
diff --git a/configs/restorers/srcnn/README_zh-CN.md b/configs/restorers/srcnn/README_zh-CN.md
index 469aaa62bf..8948ff21f7 100644
--- a/configs/restorers/srcnn/README_zh-CN.md
+++ b/configs/restorers/srcnn/README_zh-CN.md
@@ -18,3 +18,12 @@
```
+
+
+
+Evaluated on RGB channels, `scale` pixels in each border are cropped before evaluation.
+The metrics are `PSNR / SSIM` .
+
+| Method | Set5 | Set14 | DIV2K | Download |
+| :-------------------------------------------------------------------------------------: | :--------------: | :---------------: | :--------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [srcnn_x4k915_1x16_1000k_div2k](/configs/restorers/srcnn/srcnn_x4k915_g1_1000k_div2k.py) | 28.4316 / 0.8099 | 25.6486 / 0.7014 | 27.7460 / 0.7854 | [model](https://download.openmmlab.com/mmediting/restorers/srcnn/srcnn_x4k915_1x16_1000k_div2k_20200608-4186f232.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/srcnn/srcnn_x4k915_1x16_1000k_div2k_20200608_120159.log.json) |
diff --git a/configs/restorers/srresnet_srgan/README_zh-CN.md b/configs/restorers/srresnet_srgan/README_zh-CN.md
index 6f68a3770e..6d6be6d2e5 100644
--- a/configs/restorers/srresnet_srgan/README_zh-CN.md
+++ b/configs/restorers/srresnet_srgan/README_zh-CN.md
@@ -14,3 +14,14 @@
```
+
+
+
+Evaluated on RGB channels, `scale` pixels in each border are cropped before evaluation.
+
+The metrics are `PSNR / SSIM` .
+
+| Method | Set5 | Set14 | DIV2K | Download |
+| :---------------------------------------------------------------------------------------------------------: | :---------------: | :--------------: | :--------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [msrresnet_x4c64b16_1x16_300k_div2k](/configs/restorers/srresnet_srgan/msrresnet_x4c64b16_g1_1000k_div2k.py) | 30.2252 / 0.8491 | 26.7762 / 0.7369 | 28.9748 / 0.8178 | [model](https://download.openmmlab.com/mmediting/restorers/srresnet_srgan/msrresnet_x4c64b16_1x16_300k_div2k_20200521-61556be5.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/srresnet_srgan/msrresnet_x4c64b16_1x16_300k_div2k_20200521_110246.log.json) |
+| [srgan_x4c64b16_1x16_1000k_div2k](/configs/restorers/srresnet_srgan/srgan_x4c64b16_g1_1000k_div2k.py) | 27.9499 / 0.7846 | 24.7383 / 0.6491 | 26.5697 / 0.7365 | [model](https://download.openmmlab.com/mmediting/restorers/srresnet_srgan/srgan_x4c64b16_1x16_1000k_div2k_20200606-a1f0810e.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/srresnet_srgan/srgan_x4c64b16_1x16_1000k_div2k_20200506_191442.log.json) |
diff --git a/configs/restorers/tdan/README_zh-CN.md b/configs/restorers/tdan/README_zh-CN.md
index fc6b8b19cb..6c94b13bbe 100644
--- a/configs/restorers/tdan/README_zh-CN.md
+++ b/configs/restorers/tdan/README_zh-CN.md
@@ -14,3 +14,61 @@
```
+
+
+
+Evaluated on Y-channel. 8 pixels in each border are cropped before evaluation.
+The metrics are `PSNR / SSIM` .
+
+| Method | Vid4 (BIx4) | SPMCS-30 (BIx4) | Vid4 (BDx4) | SPMCS-30 (BDx4) | Download |
+|:-------------------------------------------------------------------:|:---------------:|:---------------:|:---------------:|:---------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| [tdan_vimeo90k_bix4](/configs/restorers/tdan/tdan_vimeo90k_bix4.py) | **26.49/0.792** | **30.42/0.856** | 25.93/0.772 | 29.69/0.842 | [model](https://download.openmmlab.com/mmediting/restorers/tdan/tdan_vimeo90k_bix4_20210528-739979d9.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/tdan/tdan_vimeo90k_bix4_20210528_135616.log.json) |
+| [tdan_vimeo90k_bdx4](/configs/restorers/tdan/tdan_vimeo90k_bdx4.py) | 25.80/0.784 | 29.56/0.851 | **26.87/0.815** | **30.77/0.868** | [model](https://download.openmmlab.com/mmediting/restorers/tdan/tdan_vimeo90k_bdx4_20210528-c53ab844.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/tdan/tdan_vimeo90k_bdx4_20210528_122401.log.json) |
+
+**Train**
+
+
+Train Instructions
+
+You can use the following command to train a model.
+
+```shell
+./tools/dist_train.sh ${CONFIG_FILE} ${GPU_NUM} [optional arguments]
+```
+
+TDAN is trained with two stages.
+
+**Stage 1**: Train with a larger learning rate (1e-4)
+
+```shell
+./tools/dist_train.sh configs/restorers/tdan/tdan_vimeo90k_bix4_lr1e-4_400k.py 8
+```
+
+**Stage 2**: Fine-tune with a smaller learning rate (5e-5)
+
+```shell
+./tools/dist_train.sh configs/restorers/tdan/tdan_vimeo90k_bix4_ft_lr5e-5_400k.py 8
+```
+
+For more details, you can refer to **Train a model** part in [getting_started](/docs/getting_started.md#train-a-model).
+
+
+**Test**
+
+
+Test Instructions
+
+You can use the following command to test a model.
+
+```shell
+python tools/test.py ${CONFIG_FILE} ${CHECKPOINT_FILE} [--out ${RESULT_FILE}] [--save-path ${IMAGE_SAVE_PATH}]
+```
+
+Example: Test TDAN on SPMCS-30 using Bicubic downsampling.
+
+```shell
+python tools/test.py configs/restorers/tdan/tdan_vimeo90k_bix4_ft_lr5e-5_400k.py checkpoints/SOME_CHECKPOINT.pth --save_path outputs/
+```
+
+For more details, you can refer to **Inference with pretrained models** part in [getting_started](/docs/getting_started.md#inference-with-pretrained-models).
+
diff --git a/configs/restorers/tof/README_zh-CN.md b/configs/restorers/tof/README_zh-CN.md
index bcdfb5fe4b..494105bba3 100644
--- a/configs/restorers/tof/README_zh-CN.md
+++ b/configs/restorers/tof/README_zh-CN.md
@@ -18,3 +18,12 @@
```
+
+
+
+Evaluated on RGB channels.
+The metrics are `PSNR / SSIM` .
+
+| Method | Vid4 | Download |
+| :---------------------------------------------------------------------------: | :--------------: | :---------------------------------------------------------------------------------------------------: |
+| [tof_x4_vimeo90k_official](/configs/restorers/tof/tof_x4_vimeo90k_official.py) | 24.4377 / 0.7433 | [model](https://download.openmmlab.com/mmediting/restorers/tof/tof_x4_vimeo90k_official-a569ff50.pth) |
diff --git a/configs/restorers/ttsr/README_zh-CN.md b/configs/restorers/ttsr/README_zh-CN.md
index 62f89db5d3..42f9b25256 100644
--- a/configs/restorers/ttsr/README_zh-CN.md
+++ b/configs/restorers/ttsr/README_zh-CN.md
@@ -15,3 +15,13 @@
```
+
+
+
+Evaluated on RGB channels, `scale` pixels in each border are cropped before evaluation.
+The metrics are `PSNR / SSIM` .
+
+| Method | scale | CUFED | Download |
+| :---------------------------------------------------------------------------------------------: | :---: | :--------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| [ttsr-rec_x4_c64b16_g1_200k_CUFED](/configs/restorers/ttsr/ttsr-rec_x4_c64b16_g1_200k_CUFED.py) | x4 | 25.2433 / 0.7491 | [model](https://download.openmmlab.com/mmediting/restorers/ttsr/ttsr-rec_x4_c64b16_g1_200k_CUFED_20210525-b0dba584.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/ttsr/ttsr-rec_x4_c64b16_g1_200k_CUFED_20210525-b0dba584.log.json) |
+| [ttsr-gan_x4_c64b16_g1_500k_CUFED](/configs/restorers/ttsr/ttsr-gan_x4_c64b16_g1_500k_CUFED.py) | x4 | 24.6075 / 0.7234 | [model](https://download.openmmlab.com/mmediting/restorers/ttsr/ttsr-gan_x4_c64b16_g1_500k_CUFED_20210626-2ab28ca0.pth) \| [log](https://download.openmmlab.com/mmediting/restorers/ttsr/ttsr-gan_x4_c64b16_g1_500k_CUFED_20210626-2ab28ca0.log.json) |
diff --git a/configs/synthesizers/cyclegan/README_zh-CN.md b/configs/synthesizers/cyclegan/README_zh-CN.md
index 715f79b95f..0059e31202 100644
--- a/configs/synthesizers/cyclegan/README_zh-CN.md
+++ b/configs/synthesizers/cyclegan/README_zh-CN.md
@@ -15,3 +15,29 @@
```
+
+
+
+We use `FID` and `IS` metrics to evaluate the generation performance of CycleGAN.
+
+`FID` evaluation:
+
+| Dataset | [facades](/configs/synthesizers/cyclegan/cyclegan_lsgan_resnet_in_1x1_80k_facades.py) | [facades-id0](/configs/synthesizers/cyclegan/cyclegan_lsgan_id0_resnet_in_1x1_80k_facades.py) | [summer2winter](/configs/synthesizers/cyclegan/cyclegan_lsgan_resnet_in_1x1_246200_summer2winter.py) | [summer2winter-id0](/configs/synthesizers/cyclegan/cyclegan_lsgan_id0_resnet_in_1x1_246200_summer2winter.py) | winter2summer | winter2summer-id0 | [horse2zebra](/configs/synthesizers/cyclegan/cyclegan_lsgan_resnet_in_1x1_266800_horse2zebra.py) | [horse2zebra-id0](/configs/synthesizers/cyclegan/cyclegan_lsgan_id0_resnet_in_1x1_266800_horse2zebra.py) | zebra2horse | zebra2horse-id0 | average |
+| :------: | :----------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------: | :-----------: | :---------------: | :---------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------: | :---------: | :-------------: | :--------: |
+| official | 123.626 | **119.726** | 77.342 | 76.773 | **72.631** | 74.239 | **62.111** | 77.202 | **138.646** | 137.050 | 95.935 |
+| ours | **118.297** | 126.316 | **76.959** | **76.018** | 72.803 | **73.498** | 63.810 | **71.675** | 139.279 | **132.369** | **95.102** |
+
+`IS` evaluation:
+
+| Dataset | facades | facades-id0 | summer2winter | summer2winter-id0 | winter2summer | winter2summer-id0 | horse2zebra | horse2zebra-id0 | zebra2horse | zebra2horse-id0 | average |
+| :------: | :-------: | :---------: | :-----------: | :---------------: | :-----------: | :---------------: | :---------: | :-------------: | :---------: | :-------------: | :-------: |
+| official | **1.638** | 1.697 | 2.762 | **2.750** | **3.293** | 3.110 | 1.375 | **1.584** | **3.186** | **3.047** | **2.444** |
+| ours | 1.584 | **1.957** | **2.768** | 2.735 | 3.069 | **3.130** | **1.430** | 1.542 | 3.093 | 2.958 | 2.427 |
+
+Model and log downloads:
+
+| Dataset | facades | facades-id0 | summer2winter | summer2winter-id0 | horse2zebra | horse2zebra-id0 |
+| :------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| download | [model](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_facades/cyclegan_lsgan_resnet_in_1x1_80k_facades_20200524-0b877c2a.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_facades/cyclegan_lsgan_resnet_in_1x1_80k_facades_20200524_211816.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_facades_id0/cyclegan_lsgan_id0_resnet_in_1x1_80k_facades_20200524-438aa074.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_facades_id0/cyclegan_lsgan_id0_resnet_in_1x1_80k_facades_20200524_212548.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_summer2winter/cyclegan_lsgan_resnet_in_1x1_246200_summer2winter_20200524-0baeaff6.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_summer2winter/cyclegan_lsgan_resnet_in_1x1_246200_summer2winter_20200524_214809.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_summer2winter_id0/cyclegan_lsgan_id0_resnet_in_1x1_246200_summer2winter_20200524-f280ecdd.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_summer2winter_id0/cyclegan_lsgan_id0_resnet_in_1x1_246200_summer2winter_20200524_215511.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_horse2zebra/cyclegan_lsgan_resnet_in_1x1_266800_horse2zebra_20200524-1b3d5d3a.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_horse2zebra/cyclegan_lsgan_resnet_in_1x1_266800_horse2zebra_20200524_220040.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_horse2zebra_id0/cyclegan_lsgan_id0_resnet_in_1x1_266800_horse2zebra_20200524-470fb8da.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/cyclegan/cyclegan_horse2zebra_id0/cyclegan_lsgan_id0_resnet_in_1x1_266800_horse2zebra_20200524_220655.log.json) |
+
+Note: With a larger identity loss, the image-to-image translation becomes more conservative, which makes less changes. The original authors did not say what is the best weight for identity loss. Thus, in addition to the default setting, we also set the weight of identity loss to 0 (denoting `id0` ) to make a more comprehensive comparison.
diff --git a/configs/synthesizers/pix2pix/README_zh-CN.md b/configs/synthesizers/pix2pix/README_zh-CN.md
index c8d9796d3e..90c0fc3ec5 100644
--- a/configs/synthesizers/pix2pix/README_zh-CN.md
+++ b/configs/synthesizers/pix2pix/README_zh-CN.md
@@ -15,3 +15,33 @@
```
+
+
+
+We use `FID` and `IS` metrics to evaluate the generation performance of pix2pix.
+
+`FID` evaluation:
+
+| Dataset | [facades](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_1x1_80k_facades.py) | [maps-a2b](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_a2b_1x1_219200_maps.py) | [maps-b2a](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_b2a_1x1_219200_maps.py) | [edges2shoes](/configs/synthesizers/pix2pix/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_186840_edges2shoes.py) | average |
+| :------: | :--------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------: | :---------: |
+| official | **119.135** | 149.731 | 102.072 | **75.774** | 111.678 |
+| ours | 127.792 | **118.552** | **92.798** | 85.413 | **106.139** |
+
+`IS` evaluation:
+
+| Dataset | facades | maps-a2b | maps-b2a | edges2shoes | average |
+| :------: | :-------: | :-------: | :-------: | :---------: | :-------: |
+| official | 1.650 | 2.529 | **3.552** | **2.766** | 2.624 |
+| ours | **1.745** | **2.689** | 3.473 | 2.747 | **2.664** |
+
+Model and log downloads:
+
+| Dataset | facades | maps-a2b | maps-b2a | edges2shoes |
+| :------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
+| download | [model](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_facades/pix2pix_vanilla_unet_bn_1x1_80k_facades_20200524-6206de67.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_facades/pix2pix_vanilla_unet_bn_1x1_80k_facades_20200524_185039.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_a2b/pix2pix_vanilla_unet_bn_a2b_1x1_219200_maps_20200524-b29c4538.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_a2b/pix2pix_vanilla_unet_bn_a2b_1x1_219200_maps_20200524_191918.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_b2a/pix2pix_vanilla_unet_bn_b2a_1x1_219200_maps_20200524-17882ec8.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_maps_b2a/pix2pix_vanilla_unet_bn_b2a_1x1_219200_maps_20200524_192641.log.json) | [model](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_edges2shoes_wo_jitter_flip/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_186840_edges2shoes_20200524-b35fa9c0.pth) \| [log](https://download.openmmlab.com/mmediting/synthesizers/pix2pix/pix2pix_edges2shoes_wo_jitter_flip/pix2pix_vanilla_unet_bn_wo_jitter_flip_1x4_186840_edges2shoes_20200524_193117.log.json) |
+
+Note: we strictly follow the [paper](http://openaccess.thecvf.com/content_cvpr_2017/papers/Isola_Image-To-Image_Translation_With_CVPR_2017_paper.pdf) setting in Section 3.3: "*At inference time, we run the generator net in exactly
+the same manner as during the training phase. This differs
+from the usual protocol in that we apply dropout at test time,
+and we apply batch normalization using the statistics of
+the test batch, rather than aggregated statistics of the training batch.*" (i.e., use model.train() mode), thus may lead to slightly different inference results every time.
diff --git a/tools/data/matting/comp1k/README_zh-CN.md b/tools/data/matting/comp1k/README_zh-CN.md
index 5c8962f68b..685afb0f9f 100644
--- a/tools/data/matting/comp1k/README_zh-CN.md
+++ b/tools/data/matting/comp1k/README_zh-CN.md
@@ -1 +1,13 @@
# 准备 Composition-1k 数据集
+
+
+
+```bibtex
+@inproceedings{xu2017deep,
+ title={Deep image matting},
+ author={Xu, Ning and Price, Brian and Cohen, Scott and Huang, Thomas},
+ booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
+ pages={2970--2979},
+ year={2017}
+}
+```