ACM SIGCOMM 2020, New York City, USA

ACM SIGCOMM 2020 Workshop on Hot Topics in Video Analytics and Intelligent Edges (HotEdgeVideo 2020)

Call for Papers

Cameras are everywhere! Analyzing live videos from these cameras has great potential to impact science and society. Enterprise cameras are deployed for a wide variety of commercial and security reasons. Consumer devices themselves have cameras with users interested in analyzing live videos from these devices. We are all living in the golden era for computer vision and AI that is being fueled by game-changing systemic infrastructure advancements, breakthroughs in machine learning, and copious training data, largely improving their range of capabilities. Live video analytics has the potential to impact a wide range of verticals ranging from public safety, traffic efficiency, infrastructure planning, entertainment, and home safety.

Analyzing live video streams is arguably the most challenging of domains for "systems-for-AI". Unlike text or numeric processing, video analytics require higher bandwidth, consume considerable compute cycles for processing, necessitate richer query semantics, and demand tighter security & privacy guarantees. Video analytics has a symbiotic relationship with edge compute infrastructure. Edge computing makes compute resources available closer to the data sources (i.e., cameras). All aspects of video analytics call to be designed “green-field”, from vision algorithms, to the systems processing stack and networking links, and hybrid edge-cloud infrastructure. Such a holistic design will enable the democratization of live video analytics such that any organization with cameras can obtain value from video analytics.

Topics of Interest

This workshop calls for research on various issues and solutions that can enable live video analytics with the role for edge computing. Topics of interest include (but not limited to) the following:
  • Low-cost video analytics
  • Deployment experience with large array of cameras
  • Storage of video data and metadata
  • Interactive querying of video streams
  • Network design for video streams
  • Hybrid cloud architectures for video processing
  • Scheduling for multi-tenant video processing
  • Training of vision neural networks
  • Edge-based processor architectures for video processing
  • Energy-efficient system design for video analytics
  • Intelligent camera designs
  • Vehicular and drone-based video analytics
  • Tools and datasets for video analytics systems
  • Novel vision applications
  • Video analytics for social good
  • Secure processing of video analytics
  • Privacy-preserving techniques for video processing

Submission Instructions

Submissions must be original, unpublished work, and not under consideration at another conference or journal. Submitted papers must be no longer than five (5) pages, including all figures, tables, followed by as many pages as necessary for bibliographic references. Submissions should be in two-column 10pt ACM format with authors names and affiliations for single-blind peer review. The workshop also solicits the submission of research, platform, and product demonstrations. Demo submission should be a summary or extended abstract describing the research to be presented, maximum one (1) page with font no smaller than 10 point size, in PDF file format. Demo submission title should begin with "Demo:".

Authors of accepted papers are expected to present their work at the workshop. Papers accepted for presentation will be published in the SIGCOMM Workshop Proceedings, and available at the ACM Digital Library. You may find these LaTeX and MS-Word templates useful in complying with the above requirements.

Submit your work at

Important Dates

  • May 11, 2020 11:59 PST

    Paper submission deadline

  • May 31, 2020 11:59 PST

    Paper acceptance notification

  • June 10, 2020 11:59 PST

    Camera-ready papers due

  • August 10, 2020


Program Committee

  • Program Committee
  • Ganesh Ananthanarayanan (co-chair)

    Microsoft Research

  • Junchen Jiang

    University of Chicago

  • Yunxin Liu (co-chair)

    Microsoft Research

  • Padmanabhan (Babu) Pillai

    Intel Labs and CMU

  • Yuanchao Shu (co-chair)

    Microsoft Research

  • Chenren Xu

    Peking University

  • Fengyuan Xu

    Nanjing University

  • Harry Xu

    University of California, Los Angeles

  • Mi Zhang

    Michigan State University