# An Open Software Suite for Event-Based Video

arXiv: https://arxiv.org/abs/2401.17151 · HTML: https://mlsanity.com/paper/2401.17151/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 20 references that are in the map.
- First posted on arXiv 30 Jan 2024.

## Builds on (most cited first, 5 of 5)

- [Event-based Vision: A Survey](https://mlsanity.com/paper/1904.08405/) (2019)
- [Learning in the Frequency Domain](https://mlsanity.com/paper/2002.12416/) (2020)
- [Bringing a Blurry Frame Alive at High Frame-Rate with an Event Camera](https://mlsanity.com/paper/1811.10180/) (2018)
- [An Asynchronous Intensity Representation for Framed and Event Video Sources](https://mlsanity.com/paper/2301.08783/) (2023)
- [Accelerated Event-Based Feature Detection and Compression for Surveillance Video Systems](https://mlsanity.com/paper/2312.08213/) (2023)

## Built on by (most cited first, 1 of 1)

- [adder-viz: Real-Time Visualization Software for Transcoding Event Video](https://mlsanity.com/paper/2508.14996/) (2025)

## Abstract (arXiv)

While traditional video representations are organized around discrete image frames, event-based video is a new paradigm that forgoes image frames altogether. Rather, pixel samples are temporally asynchronous and independent of one another. Until now, researchers have lacked a cohesive software framework for exploring the representation, compression, and applications of event-based video. I present the ADDeltaER software suite to fill this gap. This framework includes utilities for transcoding framed and multimodal event-based video sources to a common representation, rate control mechanisms, lossy compression, application support, and an interactive GUI for transcoding and playback. In this paper, I describe these various software components and their usage.