CVPR 2021 Workshop

First Workshop on

Ethical Considerations in Creative applications of Computer Vision

Virtual, June 19 - 2021

Introduction

Creative domains render a big part of modern society, having a strong influence on the economy and cultural life. Thus the impact of dismissing ethical aspects of working in creative computer vision applications and generative arts could amplify harms, such as enabling cultural appropriation, amplifying gender stereotypes in fashion, and limiting fashion to western designs. This workshop aims at creating a platform for interdisciplinary discussion among computer vision researchers, sociotechnical researchers, policy makers, social scientists and artists. In this workshop, we would like to encourage retrospective discussions, position papers on studying social impacts of research in creative applications of computer vision, ethical considerations in this domain including but not limited to artwork attributions, cultural appropriation and policies in creative AI. We also encourage technical contributions in computer vision for fashion, and creative content generation. Finally, we are proudly hosting the Art Gallery session in our workshop.

Announcement

- Discord link of the workshop
- Art Gallery is live now: https://computervisionart.com/
- Please fill out the workshop registration form
- Workshop will be hosted on discord! The link to register will be soon available!
- Program is updated and some of the talks are already on the program page!
- Paper reviews will be out in April 24!
- Paper submission deadline is extended to March 26!
- Call for submissions

Paper Submission

We encourage submissions of the following general categories:

Problem statements, introducing new areas of research within ethics in creative AI research.
Retrospectives on past creative content generation research and its ethical consequences.
Technical contributions in the context of creativity and computer vision:

This may include Computational Photography, Image and Video Synthesis, Datasets, Evaluation and Comparison of Vision Algorithms.