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20162021
most citedRethinking on Multi-Stage Networks for Human Pose Estimation

109 citations · 303 across the 11 of their papers we have counts for

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Showing 2019Show all

5 papers · 1 filter

cs.CV201915 cited

Vehicle Re-identification with Viewpoint-aware Metric Learning

Ruihang Chu, Yifan Sun, Yadong Li +3

This paper considers vehicle re-identification (re-ID) problem. The extreme viewpoint variation (up to 180 degrees) poses great challenges for existing approaches. Inspired by the…

cs.CV201925 cited

3D Dense Face Alignment via Graph Convolution Networks

Huawei Wei, Shuang Liang, Yichen Wei

Recently, 3D face reconstruction and face alignment tasks are gradually combined into one task: 3D dense face alignment. Its goal is to reconstruct the 3D geometric structure of fa…

cs.CV20193 cited

Re-Identification Supervised Texture Generation

Jian Wang, Yunshan Zhong, Yachun Li +2

The estimation of 3D human body pose and shape from a single image has been extensively studied in recent years. However, the texture generation problem has not been fully discusse…

cs.CV2019

Single Path One-Shot Neural Architecture Search with Uniform Sampling

Zichao Guo, Xiangyu Zhang, Haoyuan Mu +4

We revisit the one-shot Neural Architecture Search (NAS) paradigm and analyze its advantages over existing NAS approaches. Existing one-shot method, however, is hard to train and n…

cs.CV2019109 cited

Rethinking on Multi-Stage Networks for Human Pose Estimation

Wenbo Li, Zhicheng Wang, Binyi Yin +7

Existing pose estimation approaches fall into two categories: single-stage and multi-stage methods. While multi-stage methods are seemingly more suited for the task, their performa…