# evTransFER: A Transfer Learning Framework for Event-based Facial Expression Recognition

arXiv: https://arxiv.org/abs/2508.03609 · HTML: https://mlsanity.com/paper/2508.03609/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 30 of its 60 references that are in the map.
- First posted on arXiv 5 Aug 2025.

## Builds on (most cited first, 30 of 30)

- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [U-Net: Convolutional Networks for Biomedical Image Segmentation](https://mlsanity.com/paper/1505.04597/) (2015)
- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [Event-based Vision: A Survey](https://mlsanity.com/paper/1904.08405/) (2019)
- [High Speed and High Dynamic Range Video with an Event Camera](https://mlsanity.com/paper/1906.07165/) (2019)
- [Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades](https://mlsanity.com/paper/1507.07629/) (2015)
- [Deep Face Recognition: A Survey](https://mlsanity.com/paper/1804.06655/) (2018)
- [SLAYER: Spike Layer Error Reassignment in Time](https://mlsanity.com/paper/1810.08646/) (2018)
- [HATS: Histograms of Averaged Time Surfaces for Robust Event-based Object Classification](https://mlsanity.com/paper/1803.07913/) (2018)
- [End-to-End Learning of Representations for Asynchronous Event-Based Data](https://mlsanity.com/paper/1904.08245/) (2019)
- [Video Frame Interpolation via Adaptive Convolution](https://mlsanity.com/paper/1703.07514/) (2017)
- [Event-based Asynchronous Sparse Convolutional Networks](https://mlsanity.com/paper/2003.09148/) (2020)
- [N-ImageNet: Towards Robust, Fine-Grained Object Recognition with Event Cameras](https://mlsanity.com/paper/2112.01041/) (2021)
- [Deep Learning for Event-based Vision: A Comprehensive Survey and Benchmarks](https://mlsanity.com/paper/2302.08890/) (2023)
- [Time-Ordered Recent Event (TORE) Volumes for Event Cameras](https://mlsanity.com/paper/2103.06108/) (2021)
- [Recent Event Camera Innovations: A Survey](https://mlsanity.com/paper/2408.13627/) (2024)
- [Event Based, Near Eye Gaze Tracking Beyond 10,000Hz](https://mlsanity.com/paper/2004.03577/) (2020)
- [Temporal Binary Representation for Event-Based Action Recognition](https://mlsanity.com/paper/2010.08946/) (2020)
- [Moving Object Detection for Event-based vision using Graph Spectral Clustering](https://mlsanity.com/paper/2109.14979/) (2021)
- [Real-Time Face & Eye Tracking and Blink Detection using Event Cameras](https://mlsanity.com/paper/2010.08278/) (2020)
- [EventPoint: Self-Supervised Interest Point Detection and Description for Event-based Camera](https://mlsanity.com/paper/2109.00210/) (2021)
- [Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras](https://mlsanity.com/paper/2002.11656/) (2020)
- [Two Stream LSTM: A Deep Fusion Framework for Human Action Recognition](https://mlsanity.com/paper/1704.01194/) (2017)
- [Neuromorphic Event-based Facial Expression Recognition](https://mlsanity.com/paper/2304.06351/) (2023)
- [Event-based Face Detection and Tracking in the Blink of an Eye](https://mlsanity.com/paper/1803.10106/) (2018)
- [EV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks](https://mlsanity.com/paper/2304.07200/) (2023)
- [Spiking-Fer: Spiking Neural Network for Facial Expression Recognition With Event Cameras](https://mlsanity.com/paper/2304.10211/) (2023)
- [Neuromorphic Face Analysis: a Survey](https://mlsanity.com/paper/2402.11631/) (2024)
- [Exploring Temporal Dynamics in Event-based Eye Tracker](https://mlsanity.com/paper/2503.23725/) (2025)
- [Dual-Path Enhancements in Event-Based Eye Tracking: Augmented Robustness and Adaptive Temporal Modeling](https://mlsanity.com/paper/2504.09960/) (2025)

## Built on by (most cited first, 3 of 3)

- [Exploring Spatial-Temporal Dynamics in Event-based Facial Micro-Expression Analysis](https://mlsanity.com/paper/2508.11988/) (2025)
- [EventFace: Event-Based Face Recognition via Structure-Driven Spatiotemporal Modeling](https://mlsanity.com/paper/2604.06782/) (2026)
- [Event-based Liveness Detection using Temporal Ocular Dynamics: An Exploratory Approach](https://mlsanity.com/paper/2604.26285/) (2026)

## Abstract (arXiv)

Event-based cameras are bio-inspired sensors that asynchronously capture pixel intensity changes with microsecond latency, high temporal resolution, and high dynamic range, providing information on the spatiotemporal dynamics of a scene. We propose evTransFER, a transfer learning-based framework for facial expression recognition using event-based cameras. The main contribution is a feature extractor designed to encode facial spatiotemporal dynamics, built by training an adversarial generative method on facial reconstruction and transferring the encoder weights to the facial expression recognition system. We demonstrate that the proposed transfer learning method improves facial expression recognition compared to training a network from scratch. We propose an architecture that incorporates an LSTM to capture longer-term facial expression dynamics and introduces a new event-based representation called TIE. We evaluated the framework using both the synthetic event-based facial expression database e-CK+ and the real neuromorphic dataset NEFER. On e-CK+, evTransFER achieved a recognition rate of 93.6%, surpassing state-of-the-art methods. For NEFER, which comprises event sequence with real sensor noise and sparse activity, the proposed transfer learning strategy achieved an accuracy of up to 76.7%. In both datasets, the outcomes surpassed current methodologies and exceeded results when compared with models trained from scratch.