Image and Visual Representation Lab ‐ EPFL

Welcome to IVRL

The Image and Visual Representation Lab (IVRL) performs research that is primarily focused on the capture, analysis, and reproduction of color images. Aiming to improve everyone’s photographic experience, we develop algorithms and systems that help us understand, process, and measure images.

Our research areas are computational photography, color image processing, computer vision, and image quality.

News:

EPFL OpenDays: The Dangers of DeepFakes

Published:16.04.23 — The DeepFakes Demo will be run by Peter Grönquist and Professor Sabine Süsstrunk on EPFL OpenDays, at the BC building.

Our paper on point cloud SSL will appear in CVPR 2023

Published:14.04.23 — The paper "Spatiotemporal Self-supervised Learning for Point Clouds in the Wild" by Yanhao Wu, Tong Zhang, Wei Ke, Sabine Süsstrunk, and Mathieu Salzmann is accepted to CVPR2023.

Our paper on implicit reconstruction will appear in CVPR 2023

Published:14.04.23 — The paper "VolRecon: Volume Rendering of Signed Ray Distance Functions for Generalizable Multi-View Reconstruction" by Yufan Ren, Fangjinhua Wang, Tong Zhang, Marc Pollefeys, and Sabine Süsstrunk is accepted to CVPR2023.

Our paper on deep saliency prediction will appear in CVPR 2023

Published:16.04.23 — The paper "TempSAL-Uncovering Temporal Information for Deep Saliency Prediction" by Bahar Aydemir, Ludo Hoffstetter, Tong Zhang, Mathieu Salzmann, and Sabine Süsstrunk is accepted to CVPR2023.

Our paper on Real-Time Dynamic Texture Synthesis accepted to CVPR2023

Published:14.04.23 — The paper "DyNCA: Real-Time Dynamic Texture Synthesis Using Neural Cellular Automata" by Ehsan Pajouheshgar*, Yitao Xu*, Tong Zhang and Sabine Süsstrunk is accepted to CVPR2023.