activity
20172020
most citedA Learning-based Framework for Hybrid Depth-from-Defocus and Stereo Matching

11 citations · 20 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Adversarial Refinement Network for Human Motion Prediction

Xianjin Chao, Yanrui Bin, Wenqing Chu +6

Human motion prediction aims to predict future 3D skeletal sequences by giving a limited human motion as inputs. Two popular methods, recurrent neural networks and feed-forward dee…

cs.CV2020★ 3 cited

Adversarial Semantic Data Augmentation for Human Pose Estimation

Yanrui Bin, Xuan Cao, Xinya Chen +7

Human pose estimation is the task of localizing body keypoints from still images. The state-of-the-art methods suffer from insufficient examples of challenging cases such as symmet…

cs.CV2019★ 4 cited

Anti-Confusing: Region-Aware Network for Human Pose Estimation

Xuan Cao, Yanhao Ge, Ying Tai +5

In this work, we propose a novel framework named Region-Aware Network (RANet), which learns the ability of anti-confusing in case of heavy occlusion, nearby person and symmetric ap…

cs.CV2017★ 2 cited

Sparse Photometric 3D Face Reconstruction Guided by Morphable Models

Xuan Cao, Zhang Chen, Anpei Chen +3

We present a novel 3D face reconstruction technique that leverages sparse photometric stereo (PS) and latest advances on face registration/modeling from a single image. We observe…

cs.CV2017★ 11 cited

A Learning-based Framework for Hybrid Depth-from-Defocus and Stereo Matching

Zhang Chen, Xinqing Guo, Siyuan Li +2

Depth from defocus (DfD) and stereo matching are two most studied passive depth sensing schemes. The techniques are essentially complementary: DfD can robustly handle repetitive te…