Computer Vision News - November 2021

Computer-assisted surgery involves analyzing video feed from the surgery to provide feedback . This may be to identify structures , like organs or unsafe regions the surgeon should stay away from, or to recognize instruments to understand what the surgeon is doing. One of the biggest challenges in the surgical setting is the lack of labeled data. Obtaining labeled video data in the surgical setting, such as point correspondences over time, or training 3D information like depth or 3D positions, is especially difficult. This work aims to solve that by providing synthetically rendered, but realistic looking data, with the goal of achieving view-consistency, or long- term temporal consistency, in the generated videos . “ This work is a mix between GAN-based translation , which has been a big focus for a few years now, and the more recent field of neural rendering , ” Dominik explains. Long-Term Temporally Consistent Unpaired Video Translation from Simulated Surgical 3D Data Dominik Rivoir is a PhD student at the National Centre for Tumor Diseases, under the supervision of Stefanie Speidel. His work proposes a new approach to providing simulated 3D data in a surgical setting. It has been accepted as a poster this year and Dominik spoke to us ahead of his live Q&A session. 2 Summary Poster Presentation 4 Best of ICCV 2021