Paper Info
Title
A Deep Temporal Fusion Framework for Scene Flow Using a Learnable Motion Model and Occlusions
Abstract
Motion estimation is one of the core challenges in computer vision. With traditional dual-frame approaches, occlusions and out-of-view motions are a limiting factor, especially in the context of environmental perception for vehicles due to the large (ego-) motion of objects. Our work pro-poses a novel data-driven approach for temporal fusion of scene flow estimates in a multi-frame setup to overco...
Year
DOI
Venue
2021
10.1109/WACV48630.2021.00029
2021 IEEE Winter Conference on Applications of Computer Vision (WACV)
Keywords
DocType
ISSN
Training,Computer vision,Limiting,Motion estimation,Conferences,Neural networks,Bidirectional control
Conference
2472-6737
ISBN
Citations 
PageRank 
978-1-6654-0477-8
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
René Schuster1145.44
Christian Unger243.82
Didier Stricker31266138.03