Learning to See Through with Events

5 December 2022

Papers citing "Learning to See Through with Events"

8 / 8 papers shown

Title
Generalizing Event-Based Motion Deblurring in Real-World Scenarios Xiang Zhang Lei Yu Wentao Yang Jian-zhuo Liu Gui-Song Xia 36 19 0 11 Aug 2023
Seeing Behind Dynamic Occlusions with Event Cameras Rong Zou Manasi Muglikar Niko Messikommer Davide Scaramuzza 23 1 0 28 Jul 2023
Unveiling the Potential of Spike Streams for Foreground Occlusion Removal from Densely Continuous Views Jiyuan Zhang Shiyan Chen Yajing Zheng Zhaofei Yu Tiejun Huang 3DH 33 3 0 03 Jul 2023
NeuroCLIP: Neuromorphic Data Understanding by CLIP and SNN Yu-Zhu Guo Y. Chen Zhe Ma VLM 30 5 0 21 Jun 2023
Direct Learning-Based Deep Spiking Neural Networks: A Review Yu-Zhu Guo Xuhui Huang Zhe Ma AI4CE 77 47 0 31 May 2023
Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks Chankyu Lee Adarsh Kosta A. Z. Zhu Kenneth Chaney Kostas Daniilidis Kaushik Roy 91 160 0 14 Mar 2020
Spatial Transformer Networks Max Jaderberg Karen Simonyan Andrew Zisserman Koray Kavukcuoglu 146 7,337 0 05 Jun 2015
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,198 0 01 Sep 2014