SpikeCV is a new open-source computer vision platform for the spike camera. You can Learn more about SpikeCV here.
CVPR 2024 x 6 were accepted! Congratulations to Jiyuan Zhang, Changqing Su, Yanchen Dong, Rui Zhao, Yakun Chang, and Lin Zhu!
AAAI 2024 x 5 were accepted! Congratulations to Jiyuan Zhang, Junwei Zhao, Yanchen Dong, Rui Zhao, and Lin Zhu!
NeurIPS 2023 x 2 were accepted! Congratulations to Shiyan Chen, Jiyuan Zhang, and Lujie Xia!
ACM MM 2023 x 1 was accepted! Congratulations to Junwei Zhao!
TCSVT x 1 was accepted! Congratulations to Junwei Zhao!
TPAMI x 1 was accepted! Congratulations to Yajing Zheng!
Adding algorithm in "Learning Super-Resolution Reconstruction for High Temporal Resolution Spike Stream (TCSVT 21, Xijie Xiang)". It includes test codes for SRR.
The new version will be coming soon! The update would be included new examples for algorithms and more friendly intefaces.
The SpikeCV websit is open! Please take a glance to learne more about spiking vision!
Updating "spike simulators" in the example. It includes the version of numpy and torch.
Fix bugs about load_dat.py.
We are the research team from Peking University. To build up a community ecology for the spike vision to facilitate more users to take advantage of the spike camera, our built SpikeCV provides a variety of ultra-high-speed scene datasets, hardware interfaces, and an easy-to-use modules library. SpikeCV focuses on encapsulation for spike data, standardization for dataset interfaces, modularization for vision tasks, and real-time applications for challenging scenes, which can be used as a Python library to fulfilled most of the numerical analysis needs of researchers
“工欲善其事，必先利其器。”
《论语》
We are committed to integrating algorithms, hardware and data into a unified interface for user utilization.
We offer open-source platform to the community for development.
We offer examples for using spike cameras to solve real visual tasks.