665 citations · 1.3k across the 22 of their papers we have counts for
10 papers · 1 filter
Learning Fine-Grained Features for Pixel-wise Video Correspondences
Rui Li, Shenglong Zhou, Dong Liu
Video analysis tasks rely heavily on identifying the pixels from different frames that correspond to the same visual target. To tackle this problem, recent studies have advocated f…
Offline and Online Optical Flow Enhancement for Deep Video Compression
Chuanbo Tang, Xihua Sheng, Zhuoyuan Li +3
Video compression relies heavily on exploiting the temporal redundancy between video frames, which is usually achieved by estimating and using the motion information. The motion in…
Flow-Guided Transformer for Video Inpainting
Kaidong Zhang, Jingjing Fu, Dong Liu
We propose a flow-guided transformer, which innovatively leverage the motion discrepancy exposed by optical flows to instruct the attention retrieval in transformer for high fideli…
Attribute Artifacts Removal for Geometry-based Point Cloud Compression
Xihua Sheng, Li Li, Dong Liu +1
Geometry-based point cloud compression (G-PCC) can achieve remarkable compression efficiency for point clouds. However, it still leads to serious attribute compression artifacts, e…
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{…
Deep High-Resolution Representation Learning for Human Pose Estimation
Ke Sun, Bin Xiao, Dong Liu +1
This is an official pytorch implementation of Deep High-Resolution Representation Learning for Human Pose Estimation. In this work, we are interested in the human pose estimation p…