Papers
153 papers found
Orthogonal Transformer: An Efficient Vision Transformer Backbone with Token Orthogonalization
Huaibo Huang, Xiaoqiang Zhou, Ran He
Pale Transformer: A General Vision Transformer Backbone with Pale-Shaped Attention
Sitong Wu, Tianyi Wu, Haoru Tan et al.
CSWin Transformer: A General Vision Transformer Backbone With Cross-Shaped Windows
Xiaoyi Dong, Jianmin Bao, Dongdong Chen et al.
Dynamic Group Transformer: A General Vision Transformer Backbone with Dynamic Group Attention
Kai Liu, Tianyi Wu, Cong Liu et al.
TVLT: Textless Vision-Language Transformer
Zineng Tang, Jaemin Cho, Yixin Nie et al.
Are Vision-Language Transformers Learning Multimodal Representations? A Probing Perspective
Emmanuelle Salin, Badreddine Farah, Stéphane Ayache et al.
Think Global, Act Local: Dual-Scale Graph Transformer for Vision-and-Language Navigation
Shizhe Chen, Pierre-Louis Guhur, Makarand Tapaswi et al.
VL-InterpreT: An Interactive Visualization Tool for Interpreting Vision-Language Transformers
Estelle Aflalo, Meng Du, Shao-Yen Tseng et al.
Weakly Supervised Grounding for VQA in Vision-Language Transformers
Aisha Urooj, Hilde Kuehne, Chuang Gan et al.
KAT: A Knowledge Augmented Transformer for Vision-and-Language
Liangke Gui, Borui Wang, Qiuyuan Huang et al.
An Empirical Study of Training End-to-End Vision-and-Language Transformers
Zi-Yi Dou, Yichong Xu, Zhe Gan et al.
Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?
Mitja Nikolaus, Emmanuelle Salin, Stephane Ayache et al.
Multimodal Transformer with Variable-Length Memory for Vision-and-Language Navigation
Chuang Lin, Yi Jiang, Jianfei Cai et al.
SegViT: Semantic Segmentation with Plain Vision Transformers
Bowen Zhang, Zhi Tian, Quan Tang et al.
SAViT: Structure-Aware Vision Transformer Pruning via Collaborative Optimization
Chuanyang Zheng, zheyang li, Kai Zhang et al.
Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation
Zhiwei Hao, Jianyuan Guo, Ding Jia et al.
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial Removal
Yucheng Shi, Yahong Han, Yu-an Tan et al.
EfficientFormer: Vision Transformers at MobileNet Speed
Yanyu Li, Geng Yuan, Yang Wen et al.
VTC-LFC: Vision Transformer Compression with Low-Frequency Components
Zhenyu Wang, Hao Luo, Pichao WANG et al.
Fast Vision Transformers with HiLo Attention
Zizheng Pan, Jianfei Cai, Bohan Zhuang
Bridging the Gap Between Vision Transformers and Convolutional Neural Networks on Small Datasets
Zhiying Lu, Hongtao Xie, Chuanbin Liu et al.
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation
Yao Qin, Chiyuan Zhang, Ting Chen et al.
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition
Shoufa Chen, Chongjian GE, Zhan Tong et al.
When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture
Yichuan Mo, Dongxian Wu, Yifei Wang et al.
Green Hierarchical Vision Transformer for Masked Image Modeling
Lang Huang, Shan You, Mingkai Zheng et al.