vision transformer

ViTGAN: Training GANs with Vision Transformers ICLR 2022 ViT-NeT: Interpretable Vision Transformers with Neural Tree Decoder ICML 2022 ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation NeurIPS 2022 VTC-LFC: Vision Transformer Compression with Low-Frequency Components NeurIPS 2022 When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture NeurIPS 2022 When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism AAAI 2022 When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations ICLR 2022 Width & Depth Pruning for Vision Transformers AAAI 2022 Adder Attention for Vision Transformer NeurIPS 2021 All Tokens Matter: Token Labeling for Training Better Vision Transformers NeurIPS 2021 Analogous to Evolutionary Algorithm: Designing a Unified Sequence Model NeurIPS 2021 An Empirical Study of Training Self-Supervised Vision Transformers ICCV 2021 An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale ICLR 2021 Are Transformers more robust than CNNs? NeurIPS 2021 AST: Audio Spectrogram Transformer Interspeech 2021 Augmented Shortcuts for Vision Transformers NeurIPS 2021 AutoFormer: Searching Transformers for Visual Recognition ICCV 2021 Blending Anti-Aliasing into Vision Transformer NeurIPS 2021 Chasing Sparsity in Vision Transformers: An End-to-End Exploration NeurIPS 2021 CoAtNet: Marrying Convolution and Attention for All Data Sizes NeurIPS 2021 ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases ICML 2021 Co-Scale Conv-Attentional Image Transformers ICCV 2021 CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification ICCV 2021 CvT: Introducing Convolutions to Vision Transformers ICCV 2021 Do Vision Transformers See Like Convolutional Neural Networks? NeurIPS 2021