665 citations · 899 across the 15 of their papers we have counts for
11 papers · 1 filter
Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression
Zigang Geng, Ke Sun, Bin Xiao +2
In this paper, we are interested in the bottom-up paradigm of estimating human poses from an image. We study the dense keypoint regression framework that is previously inferior to…
Synergy Between Semantic Segmentation and Image Denoising via Alternate Boosting
Shunxin Xu, Ke Sun, Dong Liu +2
The capability of image semantic segmentation may be deteriorated due to noisy input image, where image denoising prior to segmentation helps. Both image denoising and semantic seg…
Bottom-Up Human Pose Estimation by Ranking Heatmap-Guided Adaptive Keypoint Estimates
Ke Sun, Zigang Geng, Depu Meng +4
The typical bottom-up human pose estimation framework includes two stages, keypoint detection and grouping. Most existing works focus on developing grouping algorithms, e.g., assoc…
Deep High-Resolution Representation Learning for Visual Recognition
Jingdong Wang, Ke Sun, Tianheng Cheng +9
High-resolution representations are essential for position-sensitive vision problems, such as human pose estimation, semantic segmentation, and object detection. Existing state-of-…
Improving Variational Autoencoder with Deep Feature Consistent and Generative Adversarial Training
Xianxu Hou, Ke Sun, Linlin Shen +1
We present a new method for improving the performances of variational autoencoder (VAE). In addition to enforcing the deep feature consistent principle thus ensuring the VAE output…
High-Resolution Representations for Labeling Pixels and Regions
Ke Sun, Yang Zhao, Borui Jiang +7
High-resolution representation learning plays an essential role in many vision problems, e.g., pose estimation and semantic segmentation. The high-resolution network (HRNet)~\cite{…