Name
Abstract | ||
|---|---|---|
Event cameras provide a number of benefits over traditional cameras, such as the ability to track incredibly fast motions, high dynamic range, and low power consumption. However, their application into computer vision problems, many of which are primarily dominated by deep learning solutions, has been limited by the lack of labeled training data for events. In this work, we propose a method which ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICCP51581.2021.9466265 | 2021 IEEE International Conference on Computational Photography (ICCP) |
DocType | ISSN | ISBN |
Conference | 2164-9774 | 978-1-6654-1952-9 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alex Zihao Zhu | 1 | 54 | 4.75 |
| Wang Ziyun | 2 | 0 | 0.34 |
| Khant Kaung | 3 | 0 | 0.34 |
| Konstantinos Daniilidis | 4 | 3122 | 255.45 |