mlsanityData to 14 Oct 2026

SpikeCV: Open a Continuous Computer Vision Era

arXiv 2303.11684 ↗First posted 21 Mar 2023cs.CVcited by 7

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Abstract (arXiv)

SpikeCV is a new open-source computer vision platform for the spike camera, which is a neuromorphic visual sensor that has developed rapidly in recent years. In the spike camera, each pixel position directly accumulates the light intensity and asynchronously fires spikes. The output binary spikes can reach a frequency of 40,000 Hz. As a new type of visual expression, spike sequence has high spatiotemporal completeness and preserves the continuous visual information of the external world. Taking advantage of the low latency and high dynamic range of the spike camera, many spike-based algorithms have made significant progress, such as high-quality imaging and ultra-high-speed target detection. To build up a community ecology for the spike vision to facilitate more users to take advantage of the spike camera, 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. With the advent of the open-source Python ecosystem, modules of SpikeCV can be used as a Python library to fulfilled most of the numerical analysis needs of researchers. We demonstrate the efficiency of the SpikeCV on offline inference and real-time applications. The project repository address are urlhttps://openi.pcl.ac.cn/Cordium/SpikeCV and urlhttps://github.com/Zyj061/SpikeCV

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 15 of its 68 references that are in the map. First posted on arXiv 21 Mar 2023.

Builds on

15 of 68 references.

References · 15

  1. 2017Attention Is All You Needcited by 60,361
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  3. 2019Surrogate Gradient Learning in Spiking Neural Networkscited by 626
  4. 2017Video Enhancement with Task-Oriented Flowcited by 619
  5. 2018Noise2Noise: Learning Image Restoration without Clean Datacited by 533
  6. 2019Kornia: an Open Source Differentiable Computer Vision Library for PyTorchcited by 232
  7. 2020Learning Monocular Dense Depth from Eventscited by 85
  8. 2020Event-Based Backpropagation can compute Exact Gradients for Spiking Neural Networkscited by 59
  9. 2019A Retina-inspired Sampling Method for Visual Texture Reconstructioncited by 34
  10. 2021Optical Flow Estimation for Spiking Cameracited by 29
  11. 20221000x Faster Camera and Machine Vision with Ordinary Devicescited by 25
  12. 2020Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networkscited by 23
3 more
  1. 2019SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applicationscited by 21
  2. 2021Spike Camera and Its Coding Methodscited by 19
  3. 2019An Efficient Coding Method for Spike Camera using Inter-Spike Intervalscited by 13

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 4; 2026: 1.

7 papers.