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cs.CV2026
RAFT-MSF++: Temporal Geometry-Motion Feature Fusion for Self-Supervised Monocular Scene Flow
Xunpei Sun, Zuoxun Hou, Yi Chang +2
Monocular scene flow estimation aims to recover dense 3D motion from image sequences, yet most existing methods are limited to two-frame inputs, restricting temporal modeling and r…
cs.CV2026
UFlow: Uncertainty-Aware Unsupervised Optical Flow Estimation
Xunpei Sun, Wenwei Lin, Yi Chang +1
Unsupervised optical flow methods typically lack reliable uncertainty estimation, limiting their robustness and interpretability. We propose UFlow, the first recurrent unsupe…
cs.CV2026
Adapting Depth Anything to Adverse Imaging Conditions with Events
Shihan Peng, Yuyang Xiong, Hanyu Zhou +5
Robust depth estimation under dynamic and adverse lighting conditions is essential for robotic systems. Currently, depth foundation models, such as Depth Anything, achieve great su…