5 citations · 7 across the 5 of their papers we have counts for
7 papers · 1 filter
RAFT-MSF: Self-Supervised Monocular Scene Flow using Recurrent Optimizer
Bayram Bayramli, Junhwa Hur, Hongtao Lu
Learning scene flow from a monocular camera still remains a challenging task due to its ill-posedness as well as lack of annotated data. Self-supervised methods demonstrate learnin…
Self-Supervised Multi-Frame Monocular Scene Flow
Junhwa Hur, Stefan Roth
Estimating 3D scene flow from a sequence of monocular images has been gaining increased attention due to the simple, economical capture setup. Owing to the severe ill-posedness of…
Self-Supervised Monocular Scene Flow Estimation
Junhwa Hur, Stefan Roth
Scene flow estimation has been receiving increasing attention for 3D environment perception. Monocular scene flow estimation -- obtaining 3D structure and 3D motion from two tempor…
Optical Flow Estimation in the Deep Learning Age
Junhwa Hur, Stefan Roth
Akin to many subareas of computer vision, the recent advances in deep learning have also significantly influenced the literature on optical flow. Previously, the literature had bee…
Iterative Residual Refinement for Joint Optical Flow and Occlusion Estimation
Junhwa Hur, Stefan Roth
Deep learning approaches to optical flow estimation have seen rapid progress over the recent years. One common trait of many networks is that they refine an initial flow estimate e…
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…