FrameCorr: Adaptive, Autoencoder-based Neural Compression for Video Reconstruction in Resource and Timing Constrained Network Settings
Year: 2024
Type: conference-paper
Abstract: Video processing is becoming increasingly popular and cost-effective on IoT devices but faces challenges in transmitting data under varying timing constraints and network bandwidth. Existing compression methods struggle with incomplete data. We present FrameCorr, a deep learning framework that leverages prior-received video data to predict and reconstruct missing frame segments, enabling video reconstruction despite data loss.
Authors: John Li, Deepak Nair, Klara Nahrstedt, Indranil Gupta, Shehab Sarar Ahmed
Institution: University of Illinois Urbana-Champaign
Language: English
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4408897862