2021-10-17 08:00 Pacific Time
Live Stream Playback at: https://youtu.be/7aYgLALc_24
ICCV 2021 Workshop on AI for Creative Video Editing and Understanding.
This workshop is for the 1st installment of the AI for Creative Video Editing and Understanding (CVEU).
The workshop brings together researchers 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 video understanding in the realm of video creation and editing. Some of the topics that we plan to discuss are:
Schedule | Pacific Time 2021-10-17 08:00 AM |
|
---|---|---|
Introduction | 08:00 AM - 08:30 AM | - |
Keynote I (by Prof. James E. Cutting)
The Event Structure of Popular Movies |
08:30 AM - 09:15 AM | - |
Keynote II (by Prof. Marc Christie)
Towards Computational Cinematography: what's left and what right? |
09:15 AM - 10:00 AM | - |
Break | 10:00 AM - 10:15 AM | - |
Keynote III (by Prof. Irfan Essa)
AI for Video Creation |
10:15 AM - 11:00 AM | - |
Panel Discussion | 11:00 AM - 12:00 PM | - |
Lunch Break | 12:00 PM - 13:00 PM | - |
Keynote IV (by Prof. Angjoo Kanazawa)
Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Image |
13:00 PM - 13:45 PM | - |
Keynote V (by Prof. Maneesh Agrawala)
Making (and Breaking) Video |
13:45 PM - 14:30 PM | - |
Break | 14:30 PM - 14:45 PM | - |
Invited Works I + QA | 14:45 PM - 15:30 PM | - |
Invited Works II + QA | 15:30 PM - 16:15 PM | - |
Industry Spotlight I (by Joon-Young - Adobe)
Video Segmentation for Video Editing |
16:15 PM - 16:30 PM | - |
Industry Spotlight II (by Anastasis -
RunwayML)
Building Human-in-the-Loop Machine Learning Tools for Video Editing |
16:30 PM - 16:45 PM | - |
Industry Spotlight III (by Synopsis)
CinemaNet: Building Better Cinematic Workflows with Creative Metadata |
16:45 PM - 17:00 PM | - |
Industry Spotlight VI (by Fernando Amat Gil -
Netflix)
Can Machine Learning Assist in Making Better Trailers? |
17:00 PM - 17:15 PM | - |
Industry Spotlight V (by Xintao Wang -
Tencent ARC)
Tencent ARC: The Wonderland of Video Editing and Creation Algorithms |
17:15 PM - 17:30 PM | - |
Closing Remarks | 17:30 PM - 17:45 PM | - |
Title | Speaker | Resource |
---|---|---|
[14:45 PM - 14:55 PM] VLG-Net: Video-Language Graph Matching Network for Video Grounding | Mattia Soldan | Paper Video(YouTube) Video(Bilibili) |
[14:55 PM - 15:00 PM] Video Transformer Network | Daniel Neimark | Paper Supp Video(YouTube) Video(Bilibili) |
[15:00 PM - 15:05 PM] TSP: Temporally-Sensitive Pretraining of Video Encoders for Localization Tasks | Humam Alwassel | Paper Supp Video(YouTube) Video(Bilibili) |
[15:05 PM - 15:10 PM] Face, Body, Voice: Video Person-Clustering with Multiple Modalities | Andrew Brown | Paper Video(YouTube) Video(Bilibili) |
[15:10 PM - 15:15 PM] Video Contrastive Learning with Global Context | Haofei Kuang | Paper Video(YouTube) Video(Bilibili) |
[15:15 PM - 15:20 PM] Plots to Previews: Towards Automatic Movie Preview Retrieval using Publicly Available Meta-data | Bhagyashree Gaikwad | Paper Supp Video(YouTube) Video(Bilibili) |
[15:20 PM - 15:25 PM] Learning Where to Cut from Edited Videos | Yuzhong Huang | Paper Video(YouTube) Video(Bilibili) |
[15:25 PM - 15:30 PM] QA | ||
[15:30 PM - 15:42 PM] Paint Transformer: Feed Forward Neural Painting with Stroke Prediction | Songhua Liu | Paper Video(YouTube) Video(Bilibili) |
[15:42 PM - 15:47 PM] Boundary-sensitive Pre-training for Temporal Localization in Videos | Mengmeng Xu | Paper Video(YouTube) Video(Bilibili) |
[15:47 PM - 15:52 PM] Editing like Humans: A Contextual, Multimodal Framework for Automated Video Editing | Patrick Adelman | Paper Video(YouTube) Video(Bilibili) |
[15:52 PM - 15:57 PM] ASCNet: Self-supervised Video Representation Learning with Appearance-Speed Consistency | Wenhao Wu | Paper Video(YouTube) Video(Bilibili) |
[15:57 PM - 16:02 PM] AniVid: A Novel Anime Video Dataset with Applications in Animation | Kai E Gangi | Paper Video(YouTube) Video(Bilibili) |
[16:02 PM - 16:06 PM] High-Level Features for Movie Style Understanding | Robin Courant | Paper Supp Video(YouTube) Video(Bilibili) |
[16:06 PM - 16:10 PM] Re-enacting video shots with fictional characters | Joanna Materzynska | Paper Video(YouTube) Video(Bilibili) |
[16:10 PM - 16:15 PM] QA |
$1,000 USD for best paper awards!
This workshop is for the 1st installment of the AI for Creative Video Editing and Understanding (CVEU). The workshop brings together researchers working on computer vision, machine listening, 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. The workshop will include invited talks by experts in the area and give the community opportunities to share their work via oral and poster presentations. We encourage practitioners, designers, students, post-docs, and researchers to submit work describing new ideas, work-in-progress, and previously or concurrently published research. Topics of interest include but are not limited to:
The Extended Abstract Track welcomes papers on the topics summarized above. The articles submitted to this track will not be published in conjunction with ICCV 2021 proceedings. So that you could submit it to other conferences or journals. All the accepted papers have opportunities to be presented during the workshop.
The papers submitted to the Extended Abstract track must be unpublished and original work related to topics of the CVEU workshop. The papers are limited to *four (4)* pages, including figures and tables, formatted according to the ICCV style. Additional pages containing only cited references are allowed. All the submitted papers will go through a double-blind peer review process with no rebuttal or second review cycle. The accepted papers will not be published in conjunction with the ICCV 2021 proceedings.
For detailed formatting instructions, and LaTeX templates please refer to the ICCV Submission Guidelines.
All the paper submission will be handled by Microsoft CMT. Please submit your paper to our CVEU CMT Console. (Please select the Extended Abstract Track)
The Invited Submission Track welcomes published papers on the topics summarized above. We will invite the accpeted papers to be presented during the workshop.
The papers submitted to the Invited Submission Track must be published work (e.g., accepted by ICCV 2021) related to topics of the CVEU workshop. All the submitted papers will have the opportunities to be presented during the workshop.
Please complete this Google Form to submit your paper.
The CVEU workshop welcomes papers on the topics summarized above. We will publish articles in conjunction with ICCV 2021 proceedings. All the accepted papers have opportunities to be presented as orals or posters during the workshop.
The papers submitted to the In-Proceedings track must be unpublished and original work related to topics of the CVEU workshop. The papers are limited to eight (8) pages, including figures and tables, formatted according to the ICCV style. Additional pages containing only cited references are allowed. All the submitted papers will go through a double-blind peer review process with no rebuttal or second review cycle. The accepted papers will be published in conjunction with the ICCV 2021 proceedings.
For detailed formatting instructions, and LaTeX templates please refer to the ICCV Submission Guidelines.
All the paper submission will be handled by Microsoft CMT. Please submit your paper to our CVEU CMT Console.