The AI for Content Creation (AICC) workshop at CVPR 2021 brings together researchers in computer vision, machine learning, and AI. Content creation has several important applications ranging from virtual reality, videography, gaming, and even retail and advertising. The recent progress of deep learning and machine learning techniques allowed to turn hours of manual, painstaking content creation work into minutes or seconds of automated work. For instance, generative adversarial networks (GANs) have been used to produce photorealistic images of items such as shoes, bags, and other articles of clothing, interior/industrial design, and even computer games' scenes. Neural networks can create impressive and accurate slow-motion sequences from videos captured at standard frame rates, thus side-stepping the need for specialized and expensive hardware. Style transfer algorithms can convincingly render the content of one image with the style of another, offering unique opportunities for generating additional and more diverse training data---in addition to creating awe-inspiring, artistic images. Learned priors can also be combined with explicit geometric constraints, allowing for realistic and visually pleasing solutions to traditional problems such as novel view synthesis, in particular for the more complex cases of view extrapolation.
AI for content creation lies at the intersection of the graphics, the computer vision, and the design community. However, researchers and professionals in these fields may not be aware of its full potential and inner workings. As such, the workshop is comprised of two parts: techniques for content creation and applications for content creation. The workshop has three goals:
More broadly, we hope that the workshop will serve as a forum to discuss the latest topics in content creation and the challenges that vision and learning researchers can help solve.
Deqing Sun (Google),
Sanja Fidler (UToronto / NVIDIA),
Lu Jiang (Google),
Angjoo Kanazawa (UC Berkeley),
Ming-Yu Liu (NVIDIA),
Cynthia Lu (Adobe),
Kalyan Sunkavalli (Adobe),
James Tompkin (Brown),
Weilong Yang (Waymo).
|Time PDT||Repeat viewing|
|08:45||20:45||Welcome and introductions|
|09:00||21:00||Speaker slot TBD|
|10:00||22:00||Speaker slot TBD|
|10:45||22:45||Speaker slot TBD|
|11:15||23:15||Speaker slot TBD|
|11:45||23:45||Poster session 1 / breakout Zoom sessions|
|13:30||01:30 (26th)||Best paper talk|
|14:00||02:00 (26th)||Speaker slot TBD|
|14:30||02:30 (26th)||Coffee break|
|14:45||02:45 (26th)||Speaker slot TBD|
|15:15||03:15 (26th)||Speaker slot TBD|
|15:45||03:45 (26th)||Coffee break|
|16:00||04:00 (26th)||Poster session 2 / breakout Zoom sessions|
|17:00||05:00 (26th)||Best poster announcement and closing|
We call for papers (8 pages not including references) and extended abstracts (4 pages not including references) to be showcased in a poster session, and for interactive demos, both for the AI for Content Creation Workshop at CVPR 2021. Authors of accepted papers and extended abstracts will be asked to post their submissions on arXiv. Both papers and extended abstracts will not be included in the proceedings of CVPR 2021, but authors should be aware that computer vision conferences consider peer-reviewed works with >4-pages to be in violation of double submission policies, e.g., both CVPR and ECCV. We will accept work in progress, work that has not been published elsewhere, and work that has been recently published elsewhere including at CVPR 2021. In the interests of fostering a free exchange of ideas, we welcome both novel and previously-published work.
Paper submissions are double blind and in the CVPR template.
Paper submission deadline:
March 8th March 29th 2021 11:59 PST
Acceptance notification: ~April 19th 2021
Submission Website: https://cmt3.research.microsoft.com/AICC2021/
The best student paper will be acknowledged with a prize of an NVIDIA GPU (kindly provided by our sponsors).
We seek contributions across content creation, including but not limited to:
This includes domains and applications for content creation: