Deep Learning-based Event Data Coding: A Joint Spatiotemporal and Polarity Solution

ArXi:2502.03285v2 Announce Type: replace Neuromorphic vision sensors, commonly referred to as event cameras, generate a massive number of pixel-level events, composed by spatiotemporal and polarity information, thus demanding highly efficient coding solutions. Existing solutions focus on lossless coding of event data, assuming that no distortion is acceptable for the target use cases, mostly including computer vision tasks such as classification and recognition.