# EventNet: Asynchronous Recursive Event Processing

arXiv: https://arxiv.org/abs/1812.07045 · HTML: https://mlsanity.com/paper/1812.07045/

## Key facts

- Cited by 58 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Dec 2018.

## Built on by (most cited first, 30 of 58)

- [AEGNN: Asynchronous Event-based Graph Neural Networks](https://mlsanity.com/paper/2203.17149/) (2022)
- [From Chaos Comes Order: Ordering Event Representations for Object Recognition and Detection](https://mlsanity.com/paper/2304.13455/) (2023)
- [Graph-based Asynchronous Event Processing for Rapid Object Recognition](https://mlsanity.com/paper/2308.14419/) (2023)
- [E2(GO)MOTION: Motion Augmented Event Stream for Egocentric Action Recognition](https://mlsanity.com/paper/2112.03596/) (2021)
- [Event Transformer. A sparse-aware solution for efficient event data processing](https://mlsanity.com/paper/2204.03355/) (2022)
- [Hierarchical Neural Memory Network for Low Latency Event Processing](https://mlsanity.com/paper/2305.17852/) (2023)
- [A Voxel Graph CNN for Object Classification with Event Cameras](https://mlsanity.com/paper/2106.00216/) (2021)
- [Pushing the Limits of Asynchronous Graph-based Object Detection with Event Cameras](https://mlsanity.com/paper/2211.12324/) (2022)
- [SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition](https://mlsanity.com/paper/2310.07189/) (2023)
- [Ev-TTA: Test-Time Adaptation for Event-Based Object Recognition](https://mlsanity.com/paper/2203.12247/) (2022)
- [Representation Learning for Event-based Visuomotor Policies](https://mlsanity.com/paper/2103.00806/) (2021)
- [Event-Based Eye Tracking. AIS 2024 Challenge Survey](https://mlsanity.com/paper/2404.11770/) (2024)
- [Rethinking Efficient and Effective Point-based Networks for Event Camera Classification and Regression: EventMamba](https://mlsanity.com/paper/2405.06116/) (2024)
- [Event Voxel Set Transformer for Spatiotemporal Representation Learning on Event Streams](https://mlsanity.com/paper/2303.03856/) (2023)
- [Event-based Simultaneous Localization and Mapping: A Comprehensive Survey](https://mlsanity.com/paper/2304.09793/) (2023)
- [A Simple and Effective Point-based Network for Event Camera 6-DOFs Pose Relocalization](https://mlsanity.com/paper/2403.19412/) (2024)
- [Learning Asynchronous and Sparse Human-Object Interaction in Videos](https://mlsanity.com/paper/2103.02758/) (2021)
- [Event Transformer+. A multi-purpose solution for efficient event data processing](https://mlsanity.com/paper/2211.12222/) (2022)
- [SPADES: A Realistic Spacecraft Pose Estimation Dataset using Event Sensing](https://mlsanity.com/paper/2311.05310/) (2023)
- [TTPOINT: A Tensorized Point Cloud Network for Lightweight Action Recognition with Event Cameras](https://mlsanity.com/paper/2308.09993/) (2023)
- [EV-Flying: an Event-based Dataset for In-The-Wild Recognition of Flying Objects](https://mlsanity.com/paper/2506.04048/) (2025)
- [Distractor-aware Event-based Tracking](https://mlsanity.com/paper/2310.14194/) (2023)
- [ALERT-Transformer: Bridging Asynchronous and Synchronous Machine Learning for Real-Time Event-based Spatio-Temporal Data](https://mlsanity.com/paper/2402.01393/) (2024)
- [A Dynamic Graph CNN with Cross-Representation Distillation for Event-Based Recognition](https://mlsanity.com/paper/2302.04177/) (2023)
- [Embedded Graph Convolutional Networks for Real-Time Event Data Processing on SoC FPGAs](https://mlsanity.com/paper/2406.07318/) (2024)
- [Learning Bottleneck Transformer for Event Image-Voxel Feature Fusion based Classification](https://mlsanity.com/paper/2308.11937/) (2023)
- [An Asynchronous Linear Filter Architecture for Hybrid Event-Frame Cameras](https://mlsanity.com/paper/2309.01159/) (2023)
- [Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-based Vision](https://mlsanity.com/paper/2401.04988/) (2024)
- [Learning Normal Flow Directly From Event Neighborhoods](https://mlsanity.com/paper/2412.11284/) (2024)
- [Event-Based Eye Tracking. 2025 Event-based Vision Workshop](https://mlsanity.com/paper/2504.18249/) (2025)

## Abstract (arXiv)

Event cameras are bio-inspired vision sensors that mimic retinas to asynchronously report per-pixel intensity changes rather than outputting an actual intensity image at regular intervals. This new paradigm of image sensor offers significant potential advantages; namely, sparse and non-redundant data representation. Unfortunately, however, most of the existing artificial neural network architectures, such as a CNN, require dense synchronous input data, and therefore, cannot make use of the sparseness of the data. We propose EventNet, a neural network designed for real-time processing of asynchronous event streams in a recursive and event-wise manner. EventNet models dependence of the output on tens of thousands of causal events recursively using a novel temporal coding scheme. As a result, at inference time, our network operates in an event-wise manner that is realized with very few sum-of-the-product operations---look-up table and temporal feature aggregation---which enables processing of 1 mega or more events per second on standard CPU. In experiments using real data, we demonstrated the real-time performance and robustness of our framework.