24 citations · 63 across the 7 of their papers we have counts for
8 papers
Step by Step Network
Dongchen Han, Tianzhu Ye, Zhuofan Xia +4
Scaling up network depth is a fundamental pursuit in neural architecture design, as theory suggests that deeper models offer exponentially greater capability. Benefiting from the r…
Linear Differential Vision Transformer: Learning Visual Contrasts via Pairwise Differentials
Yifan Pu, Jixuan Ying, Qixiu Li +7
Vision Transformers (ViTs) have become a universal backbone for both image recognition and image generation. Yet their Multi-Head Self-Attention (MHSA) layer still performs a quadr…
Differential Transformer
Tianzhu Ye, Li Dong, Yuqing Xia +4
Transformer tends to overallocate attention to irrelevant context. In this work, we introduce Diff Transformer, which amplifies attention to the relevant context while canceling no…
FAAC: Facial Animation Generation with Anchor Frame and Conditional Control for Superior Fidelity and Editability
Linze Li, Sunqi Fan, Hengjun Pu +6
Over recent years, diffusion models have facilitated significant advancements in video generation. Yet, the creation of face-related videos still confronts issues such as low facia…
Agent Attention: On the Integration of Softmax and Linear Attention
Dongchen Han, Tianzhu Ye, Yizeng Han +5
The attention module is the key component in Transformers. While the global attention mechanism offers high expressiveness, its excessive computational cost restricts its applicabi…
Joint Token Pruning and Squeezing Towards More Aggressive Compression of Vision Transformers
Siyuan Wei, Tianzhu Ye, Shen Zhang +2
Although vision transformers (ViTs) have shown promising results in various computer vision tasks recently, their high computational cost limits their practical applications. Previ…
Slide-Transformer: Hierarchical Vision Transformer with Local Self-Attention
Xuran Pan, Tianzhu Ye, Zhuofan Xia +2
Self-attention mechanism has been a key factor in the recent progress of Vision Transformer (ViT), which enables adaptive feature extraction from global contexts. However, existing…
Contrastive Language-Image Pre-Training with Knowledge Graphs
Xuran Pan, Tianzhu Ye, Dongchen Han +2
Recent years have witnessed the fast development of large-scale pre-training frameworks that can extract multi-modal representations in a unified form and achieve promising perform…