The DARING project’s aim is to develop state-of-the-art deep learning methods that are able to determine a compact image representation model, obtained (learned) from a large amount of visual data, and are capable of representing the wide variety of visual content that is available today with a high value of compression ratio. This project will advance existing solutions in the learning-based image coding field, which already show encouraging results in terms of rate- distortion performance, especially in comparison with conventional image codecs (e.g. JPEG 2000 and HEVC Intra) that compress the visual information with hand-crafted transforms, entropy coding and quantization schemes.
|Start Date: 01-10-2020|
|End Date: 01-10-2022|
|Team: João Miguel Duarte Ascenso, Catarina Isabel Carvalheiro Brites Ascenso, Nuno Miguel Morais Rodrigues, Luís Filipe Barbosa de Almeida Alexandre|
|Groups: Multimedia Signal Processing – Lx, Multimedia Signal Processing – Lr, Pattern and Image Analysis – Cv|
|Local Coordinator: João Miguel Duarte Ascenso|