Lecturer & Senior postdoc at Computer Vision Lab, ETH Zürich | Dr. Sciences ETH Zürich in Electrical Engineering and IT | MSc in Computer Science, ETH Zürich
Joined April 2021
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Christos Sakaridis retweeted
Monocular depth estimation is “impossible” because one image can’t measure depth geometrically. Our iDisc #CVPR2023 can group pixels w/o supervision and learn depth inductive bias on groups. We get LiDAR-like (but denser) depth from single images! More: vis.xyz/pub/idisc
I am pleased to give a talk at the #ICLR2023 Scene Representations for Autonomous Driving Workshop on "Optimizing internal network representations for geometric and semantic perception" and present our latest works in this direction
iclr.cc/virtual/2023/worksho…
live.bilibili.com/27720575
Check out our #CVPR2022 paper
"P3Depth: Monocular Depth Estimation with a Piecewise Planarity Prior".
Paper: openaccess.thecvf.com/conten…
Code: github.com/SysCV/P3Depth
Poster @ CVPR: 21/6, 10:00AM - 12:30PM (CST), Halls B2-C
My co-authors: Vaishakh Patil, @alexliniger, Luc Van Gool
Christos Sakaridis retweeted
I am happy to announce that the code for our @CVPR paper "LiDAR Snowfall Simulation for Robust 3D Object Detection" is now publicly available for non-commercial use: github.com/SysCV/LiDAR_snow_…
#LiDAR #snowfall #simulation
#oral: Friday, June 24th at 10:10 AM (CST) in Great Hall B-C
Christos Sakaridis retweeted
CVPR 2022: Call for Workshop Paper
Sign up: git.io/SR22
ACDC Challenge 2022 acdc.vision.ee.ethz.ch/news#… on semantic segmentation in adverse conditions is up! The challenge is held together with the CVPR'22 workshop Vision for All Seasons, it is based on the public ACDC benchmarks acdc.vision.ee.ethz.ch/bench… and it will run until Jun 3, 2022.
Christos Sakaridis retweeted
Vision for All Seasons: Adverse Weather and Lighting Conditions
7th New Trends in Image Restoration and Enhancement Workshop and Challenges
Computer Vision for Fashion, Art, and Design
Is there already a final decision on whether CVPR 2022 will be hybrid or virtual? @CVPR
Poster sessions for "ACDC: The Adverse Conditions Dataset with Correspondences for Semantic Driving Scene Understanding": Wed. Oct. 13th, 9:00 AM EDT / 3:00 PM CEST / 9:00 PM CST + Fri. Oct. 15th, 5:00 PM EDT / 11:00 PM CEST / Sat. Oct. 16th, 5:00 AM CST
2 papers accepted to #ICCV2021!
Paper 1: ACDC dataset, with Dengxin Dai and Luc Van Gool. See also: acdc.vision.ee.ethz.ch
Paper 2: Fog simulation for LiDAR-based 3D object detection, with Martin Hahner, Dengxin Dai and Luc Van Gool.
I am happy to give a talk about our new ACDC dataset in the #IV2021 workshop on Autonomy@Scale on July 11. ki-deltalearning.de/event?tx…
Christos Sakaridis retweeted
PCs update:
Thanks for your patience.
99.8% of all papers have 3 reviews completed.
We have 10 papers still to chase today.
We will release of the reviews **around 17:00 PST**, so please don't keep refreshing CMT until then. We'll announce on Twitter as promised.
Christos Sakaridis retweeted
Glad to share one of the accepted papers at CVPR2021:
- Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation - arxiv.org/pdf/2105.07830.pdf
Suman Saha, Anton Obukhov, Danda Pani Paudel, Menelaos Kanakis, Yuhua Chen, Stamatios Georgoulis, Luc Van Gool
ACDC released: a new large-scale driving dataset for training and testing semantic segmentation algorithms on adverse visual conditions, such as fog, nighttime, rain, and snow. The dataset and benchmarks are available at acdc.vision.ee.ethz.ch #computervision #autonomouscars
