198 citations · 886 across the 20 of their papers we have counts for
8 papers · 1 filter
Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao +8
Most recent semantic segmentation methods adopt a fully-convolutional network (FCN) with an encoder-decoder architecture. The encoder progressively reduces the spatial resolution a…
Improving Semantic Segmentation via Decoupled Body and Edge Supervision
Xiangtai Li, Xia Li, Li Zhang +5
Existing semantic segmentation approaches either aim to improve the object's inner consistency by modeling the global context, or refine objects detail along their boundaries by mu…
XingGAN for Person Image Generation
Hao Tang, Song Bai, Li Zhang +2
We propose a novel Generative Adversarial Network (XingGAN or CrossingGAN) for person image generation tasks, i.e., translating the pose of a given person to a desired one. The pro…
How to trust unlabeled data? Instance Credibility Inference for Few-Shot Learning
Yikai Wang, Li Zhang, Yuan Yao +1
Deep learning based models have excelled in many computer vision tasks and appear to surpass humans' performance. However, these models require an avalanche of expensive human labe…
Self-supervised Video Object Segmentation
Fangrui Zhu, Li Zhang, Yanwei Fu +2
The objective of this paper is self-supervised representation learning, with the goal of solving semi-supervised video object segmentation (a.k.a. dense tracking). We make the foll…
Style Normalization and Restitution for Generalizable Person Re-identification
Xin Jin, Cuiling Lan, Wenjun Zeng +2
Existing fully-supervised person re-identification (ReID) methods usually suffer from poor generalization capability caused by domain gaps. The key to solving this problem lies in…
Strip Pooling: Rethinking Spatial Pooling for Scene Parsing
Qibin Hou, Li Zhang, Ming-Ming Cheng +1
Spatial pooling has been proven highly effective in capturing long-range contextual information for pixel-wise prediction tasks, such as scene parsing. In this paper, beyond conven…
Few-shot Action Recognition with Permutation-invariant Attention
Hongguang Zhang, Li Zhang, Xiaojuan Qi +3
Many few-shot learning models focus on recognising images. In contrast, we tackle a challenging task of few-shot action recognition from videos. We build on a C3D encoder for spati…