most citedClothing Co-Parsing by Joint Image Segmentation and Labeling

154 citations · 449 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV201736 cited

Identity-Aware Textual-Visual Matching with Latent Co-attention

Shuang Li, Tong Xiao, Hongsheng Li +2

Textual-visual matching aims at measuring similarities between sentence descriptions and images. Most existing methods tackle this problem without effectively utilizing identity-le…

cs.CV201761 cited

Learning Feature Pyramids for Human Pose Estimation

Wei Yang, Shuang Li, Wanli Ouyang +2

Articulated human pose estimation is a fundamental yet challenging task in computer vision. The difficulty is particularly pronounced in scale variations of human body parts when c…

cs.CV2017102 cited

Multi-Context Attention for Human Pose Estimation

Xiao Chu, Wei Yang, Wanli Ouyang +3

In this paper, we propose to incorporate convolutional neural networks with a multi-context attention mechanism into an end-to-end framework for human pose estimation. We adopt sta…

cs.CV2015154 cited

Clothing Co-Parsing by Joint Image Segmentation and Labeling

Wei Yang, Ping Luo, Liang Lin

This paper aims at developing an integrated system of clothing co-parsing, in order to jointly parse a set of clothing images (unsegmented but annotated with tags) into semantic co…

cs.CV20153 cited

Learning Contour-Fragment-based Shape Model with And-Or Tree Representation

Liang Lin, Xiaolong Wang, Wei Yang +1

This paper proposes a simple yet effective method to learn the hierarchical object shape model consisting of local contour fragments, which represents a category of shapes in the f…

cs.CV201593 cited

Discriminatively Trained And-Or Graph Models for Object Shape Detection

Liang Lin, Xiaolong Wang, Wei Yang +1

In this paper, we investigate a novel reconfigurable part-based model, namely And-Or graph model, to recognize object shapes in images. Our proposed model consists of four layers:…