Accepted Papers =============== Track 1: Benchmarks, Datasets and Metrics ----------------------------------------- Contributed Talks ~~~~~~~~~~~~~~~~~ ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches. Maura Pintor, Daniele Angioni, Angelo Sotgiu, Luca Demetrio, Ambra Demontis, Battista Biggio, Fabio Roli. MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts. Weixin Liang, Xinyu Yang, James Y. Zou. When does dough become a bagel?Analyzing the remaining mistakes on ImageNet. Vijay Vasudevan, Benjamin Caine, Raphael Gontijo-Lopes, Sara Fridovich-Keil, Rebecca Roelofs. Posters ~~~~~~~ 3D Common Corruptions for Object Recognition. Oguzhan Fatih Kar, Teresa Yeo, Amir Zamir. CCC: Continuously Changing Corruptions. Ori Press, Steffen Schneider, Matthias Kuemmerer, Matthias Bethge. Classifiers Should Do Well Even on Their Worst Classes. Julian Bitterwolf, Alexander Meinke, Valentyn Boreiko, Matthias Hein. Evaluating Model Robustness to Patch Perturbations. Jindong Gu, Volker Tresp, Yao Qin. ImageNet-Cartoon and ImageNet-Drawing: two domain shift datasets for ImageNet. Tiago Salvador, Adam M Oberman. ImageNet-D: A new challenging robustness dataset inspired by domain adaptation. Evgenia Rusak, Steffen Schneider, Peter Vincent Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge. Lost in Translation: Modern Image Classifiers still degrade even under simple Translations. Leander Kurscheidt, Matthias Hein. SI-Score. Jessica Yung, Rob Romijnders, Alexander Kolesnikov, Lucas Beyer, Josip Djolonga, Neil Houlsby, Sylvain Gelly, Mario Lucic, Xiaohua Zhai. The Semantic Shift Benchmark. Sagar Vaze, Kai Han, Andrea Vedaldi, Andrew Zisserman. Track 2: Extended abstracts --------------------------- Growing ObjectNet: Adding speech, VQA, occlusion, and measuring dataset difficulty. David Mayo, David Lu, Chris Zhang, Jesse Cummings, Xinyu Lin, Boris Katz, James R. Glass, Andrei Barbu. OOD-CV: A Benchmark for Robustness to Individual Nuisances in Real-World Out-of-Distribution Shifts. Bingchen Zhao, Shaozuo Yu, Wufei Ma, Mingxin Yu, Shenxiao Mei, Angtian Wang, Ju He, Alan Yuille, Adam Kortylewski. Towards Systematic Robustness for Scalable Visual Recognition. Mohamed Omran, Bernt Schiele. Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time. Huaxiu Yao, Caroline Choi, Yoonho Lee, Pang Wei Koh, Chelsea Finn.