no code implementations • 31 Jan 2024 • Yura Perugachi-Diaz, Arwin Gansekoele, Sandjai Bhulai
Finally, we show how refinement of the latents with our best-performing method improves the compression performance on the Tecnick dataset and how it can be deployed to partly move along the rate-distortion curve.
no code implementations • 3 Mar 2022 • Yura Perugachi-Diaz, Guillaume Sautière, Davide Abati, Yang Yang, Amirhossein Habibian, Taco S Cohen
To the best of our knowledge, our proposals are the first solutions that integrate ROI-based capabilities into neural video compression models.
1 code implementation • NeurIPS 2021 • Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai
Furthermore, we propose a learnable weighted concatenation, which not only improves the model performance but also indicates the importance of the concatenated weighted representation.
no code implementations • pproximateinference AABI Symposium 2021 • Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai
We introduce Invertible Dense Networks (i-DenseNets), a more parameter efficient alternative to Residual Flows.