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Dense Monocular Motion Segmentation Using Optical Flow and Pseudo Depth
  Map: A Zero-Shot Approach

Dense Monocular Motion Segmentation Using Optical Flow and Pseudo Depth Map: A Zero-Shot Approach

27 June 2024
Yuxiang Huang
Yuhao Chen
John S. Zelek
    MDE
ArXivPDFHTML

Papers citing "Dense Monocular Motion Segmentation Using Optical Flow and Pseudo Depth Map: A Zero-Shot Approach"

5 / 5 papers shown
Title
Zero-Shot Monocular Motion Segmentation in the Wild by Combining Deep
  Learning with Geometric Motion Model Fusion
Zero-Shot Monocular Motion Segmentation in the Wild by Combining Deep Learning with Geometric Motion Model Fusion
Yuxiang Huang
Yuhao Chen
John S. Zelek
25
1
0
02 May 2024
Polyp-DAM: Polyp segmentation via depth anything model
Polyp-DAM: Polyp segmentation via depth anything model
Zhuoran Zheng
Chen Henry Wu
Wei Wang
Yeying Jin
Xiuyi Jia
VLM
10
5
0
03 Feb 2024
Guess What Moves: Unsupervised Video and Image Segmentation by
  Anticipating Motion
Guess What Moves: Unsupervised Video and Image Segmentation by Anticipating Motion
Subhabrata Choudhury
Laurynas Karazija
Iro Laina
Andrea Vedaldi
Christian Rupprecht
OCL
VOS
100
39
0
16 May 2022
Disentangling Architecture and Training for Optical Flow
Disentangling Architecture and Training for Optical Flow
Deqing Sun
Charles Herrmann
F. Reda
Michael Rubinstein
David Fleet
William T. Freeman
3DPC
OOD
53
33
0
21 Mar 2022
Learning to Segment Rigid Motions from Two Frames
Learning to Segment Rigid Motions from Two Frames
Gengshan Yang
Deva Ramanan
95
55
0
11 Jan 2021
1