42 citations · 128 across the 15 of their papers we have counts for
11 papers · 1 filter
Lightweight and Progressively-Scalable Networks for Semantic Segmentation
Yiheng Zhang, Ting Yao, Zhaofan Qiu +1
Multi-scale learning frameworks have been regarded as a capable class of models to boost semantic segmentation. The problem nevertheless is not trivial especially for the real-worl…
Dual Vision Transformer
Ting Yao, Yehao Li, Yingwei Pan +3
Prior works have proposed several strategies to reduce the computational cost of self-attention mechanism. Many of these works consider decomposing the self-attention procedure int…
Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learning
Ting Yao, Yingwei Pan, Yehao Li +2
Multi-scale Vision Transformer (ViT) has emerged as a powerful backbone for computer vision tasks, while the self-attention computation in Transformer scales quadratically w.r.t. t…
A Style and Semantic Memory Mechanism for Domain Generalization
Yang Chen, Yu Wang, Yingwei Pan +3
Mainstream state-of-the-art domain generalization algorithms tend to prioritize the assumption on semantic invariance across domains. Meanwhile, the inherent intra-domain style inv…
Transferrable Contrastive Learning for Visual Domain Adaptation
Yang Chen, Yingwei Pan, Yu Wang +3
Self-supervised learning (SSL) has recently become the favorite among feature learning methodologies. It is therefore appealing for domain adaptation approaches to consider incorpo…
CoCo-BERT: Improving Video-Language Pre-training with Contrastive Cross-modal Matching and Denoising
Jianjie Luo, Yehao Li, Yingwei Pan +3
BERT-type structure has led to the revolution of vision-language pre-training and the achievement of state-of-the-art results on numerous vision-language downstream tasks. Existing…