gyunggyung/vision-transformer-papers

Papers to look at when starting Vision Transformer 📚

🌟 Vision-Transformer-Papers 🌟

Image Classification · Semantic Segmentation
Object Detection · General Classification
Fine-Grained Image Classification · Depth Estimation
Instance Segmentation · Salient Object Detection · Person Re-Identification
GOTO PyTorch!

_{Let's find out the latest and various Vision-Transformer-related papers. 🙇‍♂️🙇‍♀️ by Stargazers}

Papers

• [2020/10] An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: ViT

• [2019/08] VISUALBERT: A SIMPLE AND PERFORMANT BASELINE FOR VISION AND LANGUAGE: VISUALBERT

• [2021/08] Boosting Salient Object Detection with Transformer-based Asymmetric Bilateral U-Net: U-Net

• [2021/03] Dynamic Feature Regularized Loss for Weakly Supervised Semantic Segmentation

• [2020/11] AdaBins: Depth Estimation using Adaptive Bins: AdaBins

• [2021/04] VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text: VATT

• [2021/05] CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification: CrossViT

• [2021/04] Emerging Properties in Self-Supervised Vision Transformers

• [2021/06] PVTv2: Improved Baselines with Pyramid Vision Transformer: PVTv2

• [2021/01] Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet: Tokens-to-Token ViT

• [2021/04] Emerging Properties in Self-Supervised Vision Transformers

• [2021/06] BEiT: BERT Pre-Training of Image Transformers: BEiT

• [2021/03] Vision Transformers for Dense Prediction

• [2021/02] TransReID: Transformer-based Object Re-Identification: TransReID

• [2021/04] All Tokens Matter: Token Labeling for Training Better Vision Transformers

• [2021/07] AutoFormer: Searching Transformers for Visual Recognition: AutoFormer

• [2021/04] Twins: Revisiting the Design of Spatial Attention in Vision Transformers: Twins

• [2021/06] You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection

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Reference

• https://huggingface.co/transformers/model_doc/vit.html
• https://paperswithcode.com/method/vision-transformer
• https://github.com/gyunggyung/NLP-Papers