650 citations · 656 across the 4 of their papers we have counts for
10 papers
CVPR19 Tracking and Detection Challenge: How crowded can it get?
Patrick Dendorfer, Hamid Rezatofighi, Anton Milan +6
Standardized benchmarks are crucial for the majority of computer vision applications. Although leaderboards and ranking tables should not be over-claimed, benchmarks often provide…
UnFlow: Unsupervised Learning of Optical Flow with a Bidirectional Census Loss
Simon Meister, Junhwa Hur, Stefan Roth
In the era of end-to-end deep learning, many advances in computer vision are driven by large amounts of labeled data. In the optical flow setting, however, obtaining dense per-pixe…
ProbFlow: Joint Optical Flow and Uncertainty Estimation
Anne S. Wannenwetsch, Margret Keuper, Stefan Roth
Optical flow estimation remains challenging due to untextured areas, motion boundaries, occlusions, and more. Thus, the estimated flow is not equally reliable across the image. To…
MirrorFlow: Exploiting Symmetries in Joint Optical Flow and Occlusion Estimation
Junhwa Hur, Stefan Roth
Optical flow estimation is one of the most studied problems in computer vision, yet recent benchmark datasets continue to reveal problem areas of today's approaches. Occlusions hav…
Robust Multi-Image HDR Reconstruction for the Modulo Camera
Florian Lang, Tobias Plötz, Stefan Roth
Photographing scenes with high dynamic range (HDR) poses great challenges to consumer cameras with their limited sensor bit depth. To address this, Zhao et al. recently proposed a…
Benchmarking Denoising Algorithms with Real Photographs
Tobias Plötz, Stefan Roth
Lacking realistic ground truth data, image denoising techniques are traditionally evaluated on images corrupted by synthesized i.i.d. Gaussian noise. We aim to obviate this unreali…