This repository serves as a comprehensive, community-driven collection of resources for event-based vision, a rapidly advancing field in computer vision and robotics. It targets researchers, engineers, and students interested in event cameras, offering a centralized hub for papers, datasets, code, workshops, and hardware information. The primary benefit is providing a structured overview and access point to the vast and growing body of knowledge in this specialized area.

How It Works

The repository is organized thematically, covering a wide spectrum of event-based vision applications and algorithms. It meticulously lists research papers, categorized by task (e.g., feature detection, optical flow, SLAM, object recognition), and provides links to hardware manufacturers, datasets, simulators, and relevant academic groups. This structure allows users to navigate the field efficiently, discover key contributions, and find practical tools and data.

Quick Start & Requirements

This is a curated list of resources, not a software package. There are no installation or execution commands. Users will need to follow links to individual papers, code repositories, or datasets, each with its own requirements.

Highlighted Details

• Extensive categorization of research papers across dozens of specific applications and algorithms.
• Comprehensive listing of event camera hardware (DVS, DAVIS, ATIS, etc.) and manufacturers.
• Links to numerous datasets, simulators, and software tools for event-based vision.
• Information on academic courses, theses, and key research groups in the field.

Maintenance & Community

The project is a community effort, with contributions from numerous researchers and institutions, notably the Institute of NeuroInformatics (INI) at the University of Zurich and ETH Zurich, iniVation AG, and Western Sydney University's ICNS. It actively tracks upcoming workshops and publications, indicating ongoing community engagement.

Licensing & Compatibility

This repository itself is a collection of links and information; it does not have a specific license. Individual linked resources (papers, code, datasets) will have their own licenses, which users must adhere to. Compatibility for commercial use or closed-source linking depends entirely on the licenses of the referenced materials.

Limitations & Caveats

As a curated list, the repository's content is dependent on community contributions and may not be exhaustive or perfectly up-to-date. The rapid pace of research means new papers and resources emerge frequently, requiring continuous updates.