Learning Dense and Continuous Optical Flow From an Event Camera
Author:
Affiliation:
1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an, China
Funder
National Natural Science Foundation of China
National Key Research and Development Program of China
Zhejiang Laboratory
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Graphics and Computer-Aided Design,Software
Link
http://xplorestaging.ieee.org/ielx7/83/9626658/09950520.pdf?arnumber=9950520
Reference66 articles.
1. Self-supervised learning of event-based optical flow with spiking neural networks;hagenaars;Proc Adv Neural Inf Process Syst (NeurIPS),2021
2. A Differentiable Recurrent Surface for Asynchronous Event-Based Data
3. Asynchronous frameless event-based optical flow
4. Volumetric correspondence networks for optical flow;yang;Proc Adv Neural Inf Process Syst (NeurIPS),2019
5. SelFlow: Self-Supervised Learning of Optical Flow
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