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FMODetect: Robust Detection of Fast Moving Objects
v1v2 (latest)

FMODetect: Robust Detection of Fast Moving Objects

IEEE International Conference on Computer Vision (ICCV), 2020
15 December 2020
D. Rozumnyi
Jirí Matas
F. Šroubek
Marc Pollefeys
Martin R. Oswald
ArXiv (abs)PDFHTML

Papers citing "FMODetect: Robust Detection of Fast Moving Objects"

5 / 5 papers shown
Benchmarking EfficientTAM on FMO datasets
Benchmarking EfficientTAM on FMO datasets
Senem Aktas
Charles Markham
John McDonald
Rozenn Dahyot
115
1
0
08 Sep 2025
Moving Object Detection from Moving Camera Using Focus of Expansion Likelihood and Segmentation
Moving Object Detection from Moving Camera Using Focus of Expansion Likelihood and Segmentation
Masahiro Ogawa
Qi An
Atsushi Yamashita
206
0
0
18 Jul 2025
FADE: A Dataset for Detecting Falling Objects around Buildings in Video
FADE: A Dataset for Detecting Falling Objects around Buildings in VideoIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2024
Zhigang Tu
Zhengbo Zhang
Zitao Gao
Chunluan Zhou
J. Yuan
Bo Du
453
2
0
11 Aug 2024
Robust Scene Inference under Noise-Blur Dual Corruptions
Robust Scene Inference under Noise-Blur Dual CorruptionsInternational Conference on Computational Photography (ICCP), 2022
Bhavya Goyal
Jean-François Lalonde
Yin Li
Mohit Gupta
NoLa
304
2
0
24 Jul 2022
Motion-from-Blur: 3D Shape and Motion Estimation of Motion-blurred
  Objects in Videos
Motion-from-Blur: 3D Shape and Motion Estimation of Motion-blurred Objects in VideosComputer Vision and Pattern Recognition (CVPR), 2021
D. Rozumnyi
Martin R. Oswald
V. Ferrari
Marc Pollefeys
3DHDiffM
283
16
0
29 Nov 2021
1
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