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HumVis: Human-Centric Visual Analysis System

  • Dongkai Wang
  • , Shiliang Zhang
  • , Yaowei Wang
  • , Yonghong Tian
  • , Tiejun Huang
  • , Wen Gao
  • Peking University
  • Peng Cheng Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Human-centric visual analysis is a fundamental task for many multimedia and computer vision applications, such as self-driving, multimedia retrieval, and augmented reality, etc. Based on our recent research efforts on fine-grained human visual analysis, we develop a robust and efficient human-centric visual analysis system named as HumVis. HumVis is built on a simple yet efficient contextual instance decoupling (CID) module, which can effectively separate different persons in an input image and output corresponding person structure information for visual analysis. Based on CID, HumVis achieves accurate multi-person pose estimation, multi-person foreground segmentation, multi-person part segmentation and 3D human mesh recovery for user-uploaded images/videos and support live stream presentation.

Original languageEnglish
Title of host publicationMM 2023 - Proceedings of the 31st ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Pages9396-9398
Number of pages3
ISBN (Electronic)9798400701085
DOIs
StatePublished - 27 Oct 2023
Externally publishedYes
Event31st ACM International Conference on Multimedia, MM 2023 - Ottawa, Canada
Duration: 29 Oct 20233 Nov 2023

Publication series

NameMM 2023 - Proceedings of the 31st ACM International Conference on Multimedia

Conference

Conference31st ACM International Conference on Multimedia, MM 2023
Country/TerritoryCanada
CityOttawa
Period29/10/233/11/23

Keywords

  • 3d human mesh recovery
  • multi-person part segmentation
  • multi-person pose estimation
  • multi-person segmentation

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