Segment moving object with moving camera by deep learning and fusion of geometric models with Huang
Segment moving object with moving camera by deep learning and fusion of geometric models with Huang
Zero-Shot Monocular Motion Segmentation in the Wild by Combining Deep Learning with Geometric Motion Model Fusion
arXiv paper abstract https://arxiv.org/abs/2405.01723
arXiv PDF paper https://arxiv.org/pdf/2405.01723
Detecting and segmenting moving objects from a moving monocular camera is challenging in ... unknown camera motion, diverse object motions and complex scene structures.
Most existing methods rely on a single motion cue to perform motion segmentation, which is usually insufficient when facing different complex environments.
... a few recent deep learning based methods are able to combine multiple motion cues to achieve improved accuracy, they depend heavily on vast datasets and extensive annotations
... propose a novel monocular dense segmentation method that achieves state-of-the-art motion segmentation results in a zero-shot manner.
... method synergestically combines the strengths of deep learning and geometric model fusion methods by performing geometric model fusion on object proposals.
... method achieves competitive results on several motion segmentation datasets and ... surpasses some state-of-the-art supervised methods ... while not ... trained on any data ...
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