Others.md

CV-News

• Semantation(new)
• Classification
• Graph Neural Networks
• Super-Resolution
• Registration
• Reconstruction
• Face
• Normalization
• Survey
• Dataset
• Conference and Journal

Classification

2019

• NIPS
  • Traned Rank Pruning for Efficient Deep Neural NetworksCode[Worksop]
• ICCV 2019
  • Domain Intersection and Domain DifferenceCode
  • Differentiable Learning-to-Group Channels via Groupable Convolutional Neural Networks
  • Embarrassingly Simple Binary Representation Learning[[Workshop]]
• TIP
  • Learning Guided Convolutional Network for Depth Completion
• MICCAI2019
  • Multi-Instance Multi-Scale CNN for Medical Image Classification
  • Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression
• Exploring Randomly Wired Neural Networks
  • Exploring Randomly Wired Neural Networks for Image Recognition（Apr 2019）[Pyroech]
  • Network Pruning via Transformable Architecture Search(May 2019)[Code]
  • AM-LFS: AutoML for Loss Function Search
  • XNAS: Neural Architecture Search with Expert Advice
• Attention Module
  • AttentionRNN: A Structured Spatial Attention Mechanism(May 2019)
• Knowledge distillation
  • Adversarially Robust Distillation
• CVPR 2019
  • SKNet:Selective Kernel Networks(Mar 2019)[Coffe][Pytorch]
  • HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs(Mar 2019)
  • Bag of Tricks for Image Classification with Convolutional Neural Networks(Dec 2018)[Code]
  • An attention-based multi-resolution model for prostate whole slide imageclassification and localization[CVPRW]
  • On-Device Neural Net Inference with Mobile GPUs[CVPRW]
• ISBI 2019
  • Improved ICH classification using task-dependent learning(29 Jun )
• ICML 2019
  • Making Convolutional Networks Shift-Invariant Again[Code]
  • Self-Attention Graph Pooling
• arXiv
  • Pruning at a Glance: Global Neural Pruning for Model Compression
  • Blockwisely Supervised Neural Architecture Search with Knowledge Distillation
  • Training convolutional neural networks with cheap convolutions and online distillation[Pytorch]
  • FALCON: Fast and Lightweight Convolution for Compressing and Accelerating CNN
  • diffGrad: An Optimization Method for Convolutional Neural Networks
  • EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks
  • EBPC: Extended Bit-Plane Compression for Deep Neural Network Inference and Training Accelerators
  • Gated Convolutional Networks with Hybrid Connectivity for Image Classification
  • A Semantics-Guided Class Imbalance Learning Model for Zero-Shot Classification
  • Multi-Path Learnable Wavelet Neural Network for Image Classification
  • Directionally Constrained Fully Convolutional Neural Network For Airborne Lidar Point Cloud Classification
  • Pay attention to the activations: a modular attention mechanism for fine-grained image recognition
  • LinearConv: Regenerating Redundancy in Convolution Filters as Linear Combinations for Parameter Reduction
  • Universal Pooling -- A New Pooling Method for Convolutional Neural Networks
  • Context-Aware Multipath Networks
  • Multi-level Wavelet Convolutional Neural Networks[Pytorch]
  • Point-Voxel CNN for Efficient 3D Deep Learning
  • AutoSlim: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates
  • Dissecting Pruned Neural Networks(29 Jun)
  • Difficulty-aware Meta-Learning for Rare Disease Diagnosis( 30 Jun )
  • Attention routing between capsules
  • Deep Saliency Models : The Quest For The Loss Function
  • Mapped Convolutions[Code]
  • Zero-Shot Image Classification Using Coupled Dictionary Embedding
  • Dense Scale Network for Crowd Counting
  • Efficient N-Dimensional Convolutions via Higher-Order Factorization
  • TensorNetwork for Machine Learning
  • A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks
  • ADA-Tucker: Compressing Deep Neural Networks via Adaptive Dimension Adjustment Tucker Decomposition
  • HGC: Hierarchical Group Convolution for Highly Efficient Neural Network
  • Visual Tree Convolutional Neural Network in Image Classification
  • DIANet: Dense-and-Implicit Attention Network[Pytorch]
  • HadaNets: Flexible Quantization Strategies for Neural Networks
  • FAN: Focused Attention Networks
  • Network Deconvolution[Pytorch]
  • SpecNet: Spectral Domain Convolutional Neural Network
  • Multi-Sample Dropout for Accelerated Training and Better Generalization
  • Spatial Group-wise Enhance: Improving Semantic Feature Learning in Convolutional Networks
  • TopoResNet: A hybrid deep learning architecture and its application to skin lesion classification(May 2019)
  • Skin Cancer Recognition using Deep Residual Network(May 2019)
  • Vehicle Shape and Color Classification Using Convolutional Neural Network(May 2019)
  • TRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes
  • ISBNet: Instance-aware Selective Branching Network
  • Convolutional neural networks with fractional order gradient method(May 2019)
  • Searching for MobileNetV3[Pytorch]
  • High Frequency Residual Learning for Multi-Scale Image Classification
  • Seesaw-Net: Convolution Neural Network With Uneven Group Convolution
  • TextCaps: Handwritten Character Recognition With Very Small Datasets(Apr 2019)[Keras][WACV]
  • Self-Attention Capsule Networks for Image Classification
  • Analytical Moment Regularizer for Gaussian Robust Networks(Apr 2019)[Pytorch]
  • Deep Sparse Representation-based Classification(Apr 2019)[Code]
  • GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond(Apr 2019)[Pytorch]
  • DenseNet Models for Tiny ImageNet Classification(Apr 2019)
  • Deep Anchored Convolutional Neural Networks(Apr 2019)
  • Stochastic Region Pooling: Make Attention More Expressive(Apr 2019)
  • Attention Augmented Convolutional Networks(Apr 2019)
  • High-Resolution Representations for Labeling Pixels and Regions(Apr 2019)
  • Deep High-Resolution Representation Learning for Human Pose Estimation(Apr 2019)[Pytorch]
  • Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution( Apr 2019)[Pytorch]
  • Convolutional Neural Networks with Layer Reuse
  • Generalizing discrete convolutions for unstructured point clouds(Apr 2019)[Pytorch]
  • Hybrid Cosine Based Convolutional Neural Networks(Apr 2019)
  • Res2Net: A New Multi-scale Backbone Architecture(Apr 2019)
  • G-softmax: Improving Intra-class Compactness and Inter-class Separability of Features(Apr 2019)
  • ANTNets: Mobile Convolutional Neural Networks for Resource Efficient Image Classification(Apr 2019)
  • A New Loss Function for CNN Classifier Based on Pre-defined Evenly-Distributed Class Centroids(Apr 2019)
  • Compressing deep neural networks by matrix product operators(Apr 2019)
  • Local Relation Networks for Image Recognition( Apr 2019)
• 3D
  • Resource Efficient 3D Convolutional Neural Networks(Apr 2019)[Code]

2017

• CVPR 2017
  • DenseNet:Densely Connected Convolutional Networks(Aug 2016)

Graph Neural Networks

• 2019
  • Neighborhood Enlargement in Graph Neural Networks(May 2019)[Pytorch]
  • A Comparison of Stereo-Matching Cost between Convolutional Neural Network and Census for Satellite Images(May 2019)

Super-Resolution

2019

• ICCV 2019
  • RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution[Code]
• CVPR 2019
  • 3D Appearance Super-Resolution with Deep Learning[Pytorch]
  • Multi-scale GANs for Memory-efficient Generation of High Resolution Medical Images
• BMVC2019
  • Gated Multiple Feedback Network for Image Super-Resolution[Code]
• Medical
  • Medical image super-resolution method based on dense blended attention network
  • Progressive Generative Adversarial Networks for Medical Image Super resolution(Feb 2019)
  • How Can We Make GAN Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach[ISBI2019]
• Arxiv
  • Multi-grained Attention Networks for Single Image Super-Resolution
  • s-LWSR: Super Lightweight Super-Resolution Network
  • Hybrid Residual Attention Network for Single Image Super Resolution
  • FC2N: Fully Channel-Concatenated Network for Single Image Super-Resolution
  • Super-Resolution of PROBA-V Images Using Convolutional Neural Networks
  • Edge-Aware Deep Image Deblurring
  • Lightweight Image Super-Resolution with Adaptive Weighted Learning Network(Apr 2019)[Code]
  • Multi-scale deep neural networks for real image super-resolution(Apr 2019)
  • Adaptive Transform Domain Image Super-resolution Via Orthogonally Regularized Deep Networks

2018

• Medical
  • Brain MRI super-resolution using 3D generative adversarial networks(Dec 2018)[MIDL][3D]
  • CT-image Super Resolution Using 3D Convolutional Neural Network(Jun 2018)[3D]
  • Super-resolution MRI through Deep Learning
  • Channel Splitting Network for Single MR Image Super-Resolution

2017

• CVPR 2017
  • Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images using Weakly-Supervised Joint Convolutional Sparse Coding(May 2017)
• MICCAI 2017
  • Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
  • DOTE: Dual cOnvolutional filTer lEarning for Super-Resolution and Cross-Modality Synthesis in MRI

Registration

• SCI
  • 3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations[[TMI]]
• ICCV
  • Recursive Cascaded Networks for Unsupervised Medical Image Registration
• MICCAI2019
  • Conv2Warp: An unsupervised deformable image registration with continuous convolution and warping
  • Closing the Gap between Deep and Conventional Image Registration using Probabilistic Dense Displacement NetworksCode
  • Probabilistic Multilayer Regularization Network for Unsupervised 3D Brain Image Registration
  • Unsupervised Deformable Image Registration Using Cycle-Consistent CNN
  • Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalization(Jul 2019)
  • Conditional Segmentation in Lieu of Image Registration(30 Jun)
• arxiv
  • Zero Shot Learning for Multi-Modal Real Time Image Registration
  • Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data(Jul 2019))
  • Robust, fast and accurate: a 3-step method for automatic histological image registration(Mar 2019)
  • 3DRegNet: A Deep Neural Network for 3D Point Registration( Apr 2019)
  • Non-Rigid Point Set Registration Networks(Apr 2019)[Pytorch]
  • Automatic Nonrigid Histological Image Registration with Adaptive Multistep Algorithm(Apr 2019)
  • Palmprint image registration using convolutional neural networks and Hough transform(Apr 2019)

Face

• 2019

Reconstruction

• 2019
  • Recon-GLGAN: A Global-Local context based Generative Adversarial Network for MRI Reconstruction[[MLMI]] +Fast Dynamic Perfusion and Angiography Reconstruction using an end-to-end 3D Convolutional Neural Network
  • Self-supervised Recurrent Neural Network for 4D Abdominal and In-utero MR Imaging

Normalization

• 2019 Positional Normalization

Survey

• 2019
  • AutoML: A Survey of the State-of-the-Art
  • A Survey on Deep Learning of Small Sample in Biomedical Image Analysis
  • Understanding Deep Learning Techniques for Image Segmentation
  • An Attentive Survey of Attention Models(Apr 2019)
  • Object Detection in 20 Years: A Survey
  • AI in the media and creative industries
  • Advancements in Image Classification using Convolutional Neural Network
  • A Review on Deep Learning in Medical Image Reconstruction
  • A Review of Point Cloud Semantic Segmentation

Dataset

Medical

• All Challenges
• SPair-71k: A Large-scale Benchmark for Semantic Correspondence
• Image Harmonization Datasets: HCOCO, HAdobe5k, HFlickr, and Hday2night
• Icentia11K: An Unsupervised Representation Learning Dataset for Arrhythmia Subtype Discovery
• RWF-2000: An Open Large Scale Video Database for Violence Detection
• A Benchmark for Anomaly Segmentation[Code]

Brain

• Brain Tissue Segmentation

  • MRBrainS2018
  • iSeg-2017 challenge:segmentation of 6-month infant brain tissues
  • NEATBrainS15
  • MRBrainS2013
  • NeoBrainS2012

• MS Lesion Segmentation

  • 2016 MS segmentation challenge
  • 2015 Longitudinal MS Lesion Segmentation Challenge
  • 2008 MS lesion segmentation challenge

• Multimodal Brain Tumor Segmentation

  • Multimodal Brain Tumor Segmentation Challenge 2018
  • Multimodal Brain Tumor Segmentation Challenge 2017
  • Multimodal Brain Tumor Segmentation Challenge 2016

• Ischemic Stroke Lesion Segmentation

  • Ischemic Stroke Lesion Segmentation (ISLES) 2018
  • Ischemic Stroke Lesion Segmentation (ISLES) 2017
  • Ischemic Stroke Lesion Segmentation (ISLES) 2016
  • Ischemic Stroke Lesion Segmentation (ISLES) 2016

• White Matter Hyperintensities

  • WMH Segmentation Challenge 2017

• EM segmentation challenge

  • ISBI Challenge: Segmentation of neuronal structures in EM stacks

Conference and Journal

Medical Image Processing Conference and Journal

Conference

MICCAI
Submission Deadline：2018-03-02
Accept/Reject Notification：

ISBI
Submission Deadline：Oct 16, 2018
Accept/Reject Notification：Dec 18, 2018

IPMI
Submission Deadline:13 December 2018
Accept/Reject Notification：25 February 2019

EMBC[CCF C]
Submission Deadline:February 19, 2019
Accept/Reject Notification：April 12, 2019

BIBM2019[CCF B]
Submission Deadline: Aug 17, 2019
Accept/Reject Notification：Oct 1, 2019

ICASSP[CCF B]
Submission Deadline:October 29
Accept/Reject Notification：February 1

MIDL
Submission Deadline:17 December 2018
Accept/Reject Notification：27 February 2019

Journal

Medical Image Analysis,MIA
IEEE Transactions on Medical Imaging,TMI

Image Processing Conference and Journal

Conference

CVPR
Submission Deadline：2018-11-16 Accept/Reject Notification： 2019-03-02

ECCV
Submission Deadline：2018-03-14
Accept/Reject Notification：2018-07-01

ICCV Submission Deadline：2019-03-15
Accept/Reject Notification2019-06-07

ICML
Submission Deadline：2019-01-18

ICLR
Submission Deadline：2018-09-27

AAAI
Submission Deadline：2018-08-30
Accept/Reject Notification：2018-11-01

NeurIPS
Submission Deadline：May 23, 2019
Accept/Reject Notification： Dec 2 - Dec 8, 2019

IJCAI
Submission Deadline：2019-02-25
Accept/Reject Notification： 2019-05-09

BMVC
BMVC2019
received 1008 submissions, of which 815 were valid. Of these, a total of 231 papers were accepted (38 as Oral Presentations, 193 as Poster Presentations). This amounts to a 28% acceptance rate

Journal