GCNet: "Global Context Networks", ICCVW, 2019 (& TPAMI 2020) ( Microsoft).AA: "Attention Augmented Convolutional Networks", ICCV, 2019 ( Google).HAT-Net: "Vision Transformers with Hierarchical Attention", arXiv, 2022 ( ETHZ).CoTNet: "Contextual Transformer Networks for Visual Recognition", CVPRW, 2021 ( JD).HaloNet: "Scaling Local Self-Attention For Parameter Efficient Visual Backbones", CVPR, 2021 ( Google).GSA: "Global Self-Attention Networks for Image Recognition", arXiv, 2020 ( Google).Axial-DeepLab: "Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation", ECCV, 2020 ( Google).SAN: "Exploring Self-attention for Image Recognition", CVPR, 2020 ( CUHK + Intel).Axial-Transformer: "Axial Attention in Multidimensional Transformers", arXiv, 2019 ( Google).SASA: "Stand-Alone Self-Attention in Vision Models", NeurIPS, 2019 ( Google).LR-Net: "Local Relation Networks for Image Recognition", ICCV, 2019 ( Microsoft).Image Classification / Backbone Replace Conv w/ Attention Pure Attention "Attention mechanisms and deep learning for machine vision: A survey of the state of the art", arXiv, 2021 ( University of Kashmir, India)."A Survey of Visual Transformers", arXiv, 2021 ( CAS)."A Survey of Transformers", arXiv, 2021 ( Fudan)."Survey: Transformer based Video-Language Pre-training", arXiv, 2021 ( Renmin University of China)."Transformers in Vision: A Survey", ACM Computing Surveys, 2021 ( MBZUAI)."Visual Attention Methods in Deep Learning: An In-Depth Survey", arXiv, 2022 ( Fayoum University, Egypt)."Image Captioning In the Transformer Age", arXiv, 2022 ( Alibaba)."Transformers Meet Visual Learning Understanding: A Comprehensive Review", arXiv, 2022 ( Xidian University)."Recent Advances in Vision Transformer: A Survey and Outlook of Recent Work", arXiv, 2022 ( ?)."Transformers in Medical Image Analysis: A Review", arXiv, 2022 ( Nanjing University)."Video Transformers: A Survey", arXiv, 2022 ( Universitat de Barcelona, Spain)."Vision Transformers in Medical Computer Vision - A Contemplative Retrospection", arXiv, 2022 ( National University of Sciences and Technology (NUST), Pakistan)."Are we ready for a new paradigm shift? A Survey on Visual Deep MLP", arXiv, 2022 ( Tsinghua)."Efficient Transformers: A Survey", arXiv, 2022 ( Google)."A survey on attention mechanisms for medical applications: are we moving towards better algorithms?", arXiv, 2022 ( INESC TEC and University of Porto, Portugal)."Transformers in 3D Point Clouds: A Survey", arXiv, 2022 ( University of Waterloo)."Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives", arXiv, 2022 ( CAS)."Multimodal Learning with Transformers: A Survey", arXiv, 2022 ( Oxford)."Transformers in Medical Imaging: A Survey", arXiv, 2022 ( MBZUAI)."Vision Transformers: State of the Art and Research Challenges", arXiv, 2022 ( NYCU)."3D Vision with Transformers: A Survey", arXiv, 2022 ( MBZUAI)."Medical image analysis based on transformer: A Review", arXiv, 2022 ( NUS, Singapore)."Transformers in Remote Sensing: A Survey", arXiv, 2022 ( MBZUAI)."VLP: A Survey on Vision-Language Pre-training", arXiv, 2022 ( CAS)."Vision Transformers for Action Recognition: A Survey", arXiv, 2022 ( Charles Sturt University, Australia)."Vision-and-Language Pretrained Models: A Survey", IJCAI, 2022 ( The University of Sydney)."A Comprehensive Study of Vision Transformers on Dense Prediction Tasks", VISAP, 2022 ( NavInfo Europe, Netherlands)."A Survey on Visual Transformer", TPAMI, 2022 ( Huawei).Transfer / X-Supervised / X-Shot / Continual Learning.Added all the related papers from CVPR 2022! Added all the related papers from ICML 2022!
Added the Transformer tutorial slides made by Lucas Beyer!
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If you find this repository useful, please consider citing and ★STARing this list.įeel free to share this list with others! If you find some ignored papers, feel free to create pull requests, open issues, or email me.Ĭontributions in any form to make this list more comprehensive are welcome. This list is maintained by Min-Hung Chen. This repo contains a comprehensive paper list of Vision Transformer & Attention, including papers, codes, and related websites.
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