We invite submissions of up to 4-page abstracts (without references) in anonymized CVPR format of current or previously published work addressing the topics outlined below. We encourage interdisciplinary work, position papers, surveys, retrospectives and other discussions addressing issues that we should consider while conducting and publishing computer vision research.

We will make the accepted submissions available on our website as non-archival reports (there will be no proceedings). The accepted works will be presented at the poster session and some will be selected for oral presentation.

Paper submission link: https://easychair.org/conferences/?conf=beyondfaircv2021

Submission deadline: Extended to April 2, 2021: 11:59pm Anywhere on Earth

Computer vision in practice: Who is benefitting and who is being harmed? We welcome submissions examining how computer vision technology intersect with, and amplifies, structural inequality and how the research practices and incentive structures within the academic field are implicated in the harms to marginalized groups. We welcome submissions that critically examine how one's own research and their roles within the community can contribute to a strengthening or dismantling of existing systems of power.

Cross-disciplinary research methods and methodologies. Computer vision is simultaneously a social and technical endeavor. Yet, current computer vision education and publication incentives tend to valorize the technical and devalue the social. This knowledge hierarchy is directly implicated in the harms being perpetuated by the field. We encourage submissions that introduce methods and methodologies that have been developed in other fields and by communities experiencing marginalization.

Accountability and transparency. The field of computer vision is currently facing a crisis of accountability. Computer vision systems are being developed and deployed at a rapid pace, often in highly socially consequential domains. Yet, computer vision models and datasets are frequently developed with little transparency into the design and development process, and few mechanisms of accountability, contestability, or recourse for individuals impacted by the systems. We encourage submissions that audit models or datasets, that examine model or dataset development processes, and that introduce frameworks that promote transparent and accountable model and dataset development (e.g. Model Cards, Datasheets). We also welcome submissions that explore ethical obligations of researchers and discuss mechanisms of ethical oversight within academic research.

Activism and collective organizing. We believe computer vision experts have an important role to play in shifting public discourse and public policy regarding the use of computer vision technologies, and shifting the research culture, norms, and incentive structures in a manner that will ultimately promote more responsible research practices. We hope to empower researchers to take an active role in all these realms. We welcome submissions that examine the institutional barriers within computer vision that are contributing to the extreme concentration of power within the field, in an effort to better diagnose the current condition of the field, and provide insights into how to best effect change.

Historical perspectives. Computer vision methods have advanced rapidly in recent years. However, many of the practical applications of computer vision methods have long histories that predate the field. These histories can provide valuable insight into the latent assumptions and ideologies underlying modern computer vision tools as well as the harms these tools can cause to marginalized groups. We encourage submissions that offer historical perspectives on the field of computer vision, including, but not limited to, histories of computer vision datasets and the trajectory of various applications across time.

• Paper submission deadline: April 2, 2021

• Notification to authors: April 23, 2021

• Camera ready deadline (uploading PDFs on our website, non-archival): May 14, 2021