# 1000x Faster Camera and Machine Vision with Ordinary Devices

arXiv: https://arxiv.org/abs/2201.09302 · HTML: https://mlsanity.com/paper/2201.09302/

## Key facts

- Cited by 25 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 26 references that are in the map.
- First posted on arXiv 23 Jan 2022.

## Builds on (most cited first, 1 of 1)

- [BP-STDP: Approximating Backpropagation using Spike Timing Dependent Plasticity](https://mlsanity.com/paper/1711.04214/) (2017)

## Built on by (most cited first, 25 of 25)

- [Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks](https://mlsanity.com/paper/2302.08890/) (2023)
- [Line-based 6-DoF Object Pose Estimation and Tracking With an Event Camera](https://mlsanity.com/paper/2408.03225/) (2024)
- [Stereo Event-based, 6-DOF Pose Tracking for Uncooperative Spacecraft](https://mlsanity.com/paper/2503.12732/) (2025)
- [Event-based Continuous Color Video Decompression from Single Frames](https://mlsanity.com/paper/2312.00113/) (2023)
- [SDTrack: A Baseline for Event-based Tracking via Spiking Neural Networks](https://mlsanity.com/paper/2503.08703/) (2025)
- [SpikeCV: Open a Continuous Computer Vision Era](https://mlsanity.com/paper/2303.11684/) (2023)
- [SpikeNeRF: Learning Neural Radiance Fields from Continuous Spike Stream](https://mlsanity.com/paper/2403.11222/) (2024)
- [SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams](https://mlsanity.com/paper/2403.09486/) (2024)
- [SpikeGS: 3D Gaussian Splatting from Spike Streams with High-Speed Camera Motion](https://mlsanity.com/paper/2407.10062/) (2024)
- [Simultaneous Enhancement and Noise Suppression under Complex Illumination Conditions](https://mlsanity.com/paper/2512.08378/) (2025)
- [SOTA: Spike-Navigated Optimal TrAnsport Saliency Region Detection in Composite-bias Videos](https://mlsanity.com/paper/2505.00394/) (2025)
- [Fast Window-Based Event Denoising with Spatiotemporal Correlation Enhancement](https://mlsanity.com/paper/2402.09270/) (2024)
- [USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting](https://mlsanity.com/paper/2411.10504/) (2024)
- [Optical Flow-Guided 6DoF Object Pose Tracking with an Event Camera](https://mlsanity.com/paper/2512.21053/) (2025)
- [SpikeMM: Flexi-Magnification of High-Speed Micro-Motions](https://mlsanity.com/paper/2406.00383/) (2024)
- [SpikeGS: Learning 3D Gaussian Fields from Continuous Spike Stream](https://mlsanity.com/paper/2409.15176/) (2024)
- [High-speed and High-quality Vision Reconstruction of Spike Camera with Spike Stability Theorem](https://mlsanity.com/paper/2412.11639/) (2024)
- [SpikeDerain: Unveiling Clear Videos from Rainy Sequences Using Color Spike Streams](https://mlsanity.com/paper/2503.20315/) (2025)
- [SPKLIP: Aligning Spike Video Streams with Natural Language](https://mlsanity.com/paper/2505.12656/) (2025)
- [SpikeStereoNet: A Brain-Inspired Framework for Stereo Depth Estimation from Spike Streams](https://mlsanity.com/paper/2505.19487/) (2025)
- [Learning to Robustly Reconstruct Low-light Dynamic Scenes from Spike Streams](https://mlsanity.com/paper/2401.10461/) (2024)
- [Seeing the Unseen in Low-light Spike Streams](https://mlsanity.com/paper/2509.23304/) (2025)
- [Spatio-Temporal Difference Guided Motion Deblurring with the Complementary Vision Sensor](https://mlsanity.com/paper/2604.10554/) (2026)
- [A Geometric Framework for Absolute Pose and Velocity Estimation with Event Cameras](https://mlsanity.com/paper/2606.09139/) (2026)
- [Neuromorphic Object Detection: An In-Depth Study and Future Directions](https://mlsanity.com/paper/2607.23576/) (2026)

## Abstract (arXiv)

In digital cameras, we find a major limitation: the image and video form inherited from a film camera obstructs it from capturing the rapidly changing photonic world. Here, we present vidar, a bit sequence array where each bit represents whether the accumulation of photons has reached a threshold, to record and reconstruct the scene radiance at any moment. By employing only consumer-level CMOS sensors and integrated circuits, we have developed a vidar camera that is 1,000x faster than conventional cameras. By treating vidar as spike trains in biological vision, we have further developed a spiking neural network-based machine vision system that combines the speed of the machine and the mechanism of biological vision, achieving high-speed object detection and tracking 1,000x faster than human vision. We demonstrate the utility of the vidar camera and the super vision system in an assistant referee and target pointing system. Our study is expected to fundamentally revolutionize the image and video concepts and related industries, including photography, movies, and visual media, and to unseal a new spiking neural network-enabled speed-free machine vision era.