LTR(Long-Tailed Recognition)

😊This file is mainly used to document papers on long tail recognition and track some of the latest research findings.

😊Class-imbalance (also known as the long-tail problem) is the fact that the classes are not represented equally in a classification problem, which is quite common in practice. For instance, fraud detection, prediction of rare adverse drug reactions and prediction gene families. Failure to account for the class imbalance often causes inaccurate and decreased predictive performance of many classification algorithms. Imbalanced learning aims to tackle the class imbalance problem to learn an unbiased model from imbalanced data. Link: https://github.com/ZhiningLiu1998/awesome-imbalanced-learning

Survey

1. [10/2021] "A Survey on Long-Tailed Visual Recognition" Link: https://arxiv.org/abs/2205.13775
2. [04/2021] "Deep Long-Tailed Learning: A Survey" Link: https://arxiv.org/abs/2110.04596

Stage-wise

1. [04/2024] "Exploring Weight Balancing on Long-Tailed Recognition Problem" Link: https://arxiv.org/abs/2305.16573
2. [03/2022] "Long-Tailed Recognition via Weight Balancing" Link: https://arxiv.org/abs/1910.09217
3. [02/2020] "Decoupling Representation and Classifier for Long-Tailed Recognition" Link: https://arxiv.org/abs/1910.09217
4. [07/2019] "Image Deformation Meta-Networks for One-Shot Learning" Link: https://arxiv.org/abs/1905.11641

Diffusion

1. [04/2024] "Latent-based Diffusion Model for Long-tailed Recognition" Link: https://arxiv.org/abs/2404.04517
2. [03/2024] "DiffuLT: How to Make Diffusion Model Useful for Long-tail Recognition" Link: https://arxiv.org/abs/2403.05170

Multimodal

1. [12/2023] "CLIP-guided Federated Learning on Heterogeneous and Long-Tailed Data" Link: https://arxiv.org/abs/2312.08648
2. [07/2022] "VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition" Link: https://arxiv.org/abs/2111.13579

Transfer learning

1. [06/2021]"RSG: A Simple but Effective Module for Learning Imbalanced Datasets" Link: https://arxiv.org/abs/2106.09859
2. [12/2020]"M2m: Imbalanced Classification via Major-to-minor Translation" Link: https://arxiv.org/abs/2004.00431
3. [06/2018]"Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning" Link: https://arxiv.org/abs/1806.06193