3 citations · 4 across the 3 of their papers we have counts for
4 papers · 1 filter
RobustSpring: Benchmarking Robustness to Image Corruptions for Optical Flow, Scene Flow and Stereo
Victor Oei, Jenny Schmalfuss, Lukas Mehl +5
Standard benchmarks for optical flow, scene flow, and stereo vision algorithms generally focus on model accuracy rather than robustness to image corruptions like noise or rain. Hen…
Distracting Downpour: Adversarial Weather Attacks for Motion Estimation
Jenny Schmalfuss, Lukas Mehl, Andrés Bruhn
Current adversarial attacks on motion estimation, or optical flow, optimize small per-pixel perturbations, which are unlikely to appear in the real world. In contrast, adverse weat…
Spring: A High-Resolution High-Detail Dataset and Benchmark for Scene Flow, Optical Flow and Stereo
Lukas Mehl, Jenny Schmalfuss, Azin Jahedi +2
While recent methods for motion and stereo estimation recover an unprecedented amount of details, such highly detailed structures are neither adequately reflected in the data of ex…
Attacking Motion Estimation with Adversarial Snow
Jenny Schmalfuss, Lukas Mehl, Andrés Bruhn
Current adversarial attacks for motion estimation (optical flow) optimize small per-pixel perturbations, which are unlikely to appear in the real world. In contrast, we exploit a r…