CVEU Workshop

2022-10-16 08:00 Pacific Time
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ECCV 2022 Workshop on AI for
Creative Video Editing and Understanding

About CVEU

This workshop is for the 2nd installment of the AI for Creative Video Editing and Understanding (CVEU), which follows its success on the first launch at ICCV2021.

The workshop brings together researchers, artists and entrepreneurs working on computer vision, machine learning, computer graphics, human computer interaction, and cognitive research.

It aims to bring awareness of recent advances in machine learning technologies to enable assisted creative-video creation and understanding.


Discuss recent advances in creative video understanding, creation and editing. Some of the topics that we plan to discuss are:

  • Can AI reduce the human cost of video productions?
  • How to design intuitive video editing tools?
  • How do humans and AI collaborate together to inspire creativity?
  • Would AI kill video editing jobs?
  • Are there any biases and threats by using AI in this field?

  • Keynote Speakers

    Tali Dekel
    Professor, Weizmann Institute of Science; Google
    Mark Riedl
    Taetle Chair and Professor, Georgia Tech
    Yagiz Aksoy
    Professor, Simon Fraser University
    Misha Tenenbaum
    CEO, EditMentor
    Pinar Seyhan Demirdag
    Co-Founder, AI Director, Seyhan Lee
    Raffay Hamid
    Senior Principal Scientist, Amazon Prime Video
    Special guests
    Negar Rostamzadeh
    Google Responsible AI
    Paul Trillo
    Creative Film Director
    Oran Gafni
    Make-A-Video, Meta
    Patrick Esser
    Stable Diffusion, Runway

    Detailed Program

    Schedule Pacific Time
    2022-10-16 08:00 AM

    Introduction   08:00 AM - 08:10 AM -
    Academia Keynote I by Tali Dekel  
    Layered Neural Atlases for Video Editing
    08:10 AM - 08:40 AM -
    Academia Keynote II by Mark Riedl  
    Computers, Creativity, and Lovelace
    08:40 AM - 09:10 AM -
    Industry Keynote I by Misha Tenenbaum  
    Reimagining Creative Video Editing Education
    09:10 AM - 09:40 AM -
    Industry Keynote II by Pinar Seyhan Demirda  
    Integration of Generative A.I. Models into Film Production
    09:40 AM - 10:10 AM -
    Roundtable I Connecting Academia and Industry  
    10:10 AM - 11:10 AM -
    Oral Paper Presentation  
    11:10 AM - 11:50 AM -
    Poster Q&A and Break  
    11:50 AM - 12:30 PM -
    Roundtable II Advanced Image Generation for Video and Art  
    12:30 PM - 01:30 PM -
    Academia Keynote III by Yagiz Aksoy  
    Interactive Depth Editing
    01:30 PM - 02:00 PM -
    Industry Keynote III by Raffay Hamid  
    Lights, Camera, AI! – How Prime Video is Inventing AI technologies to Re-define the Production and Consumption of Long-form Video Content
    02:00 PM - 02:30 PM -
    Closing Remarks   02:30 PM - 02:40 PM -

    Participants from

    Papers Presentation

    In-proceeding Track Resources
    STC: Spatio-Temporal Contrastive Learning for Video Instance Segmentation Paper   Video
    Mitigating Representation Bias in Action Recognition: Algorithms and Benchmarks Paper   Video
    SegTAD: Precise Temporal Action Detection via Semantic Segmentation Paper   Video
    Text-Driven Stylization of Video Objects Paper
    MND: A New Dataset and Benchmark of Movie Scenes Classified by their Narrative Function Paper
    Are all combinations equal? Combining textual and visual features with multiple space learning for text-based video retrieval Paper   Video
    Scene-adaptive Temporal Stabilisation for Video Colourisation using Deep Video Priors Paper   Video
    MOVIE LENS: Discovering and Characterizing Editing Patterns in the Analysis of Short Movie Sequences Paper
    Extended Abstract Track Resources
    CoolGAN: GANs with Transformers Super-Resolving Images Paper   Video
    Diffusion Models for Video Prediction and Infilling Paper
    The Same Thing Only Different: Classification of Movies by their Story Types Paper   Video
    Temporal and Contextual Transformer for Multi-Camera Editing of TV Shows Paper
    Invited Paper Track Resources
    The Anatomy of Video Editing: A Dataset and Benchmark Suite for AI-Assisted Video Editing Paper
    XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model Paper   Video
    PrivHAR: Recognizing Human Actions From Privacy-preserving Lens Paper   Video
    Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields Paper   Video


    $1,000 USD for best paper awards!

    Call for Papers


    Fabian Caba Heilbron
    Adobe Research
    Anyi Rao
    The Chinese University of Hong Kong
    Linning Xu
    The Chinese University of Hong Kong
    Yu Xiong
    The Chinese University of Hong Kong
    Ali Thabet
    Victor Escorcia
    Dong Liu
    Dahua lin
    The Chinese University of Hong Kong