4 papers
TreeNet: A Light Weight Model for Low Bitrate Image Compression
Mahadev Prasad Panda, Purnachandra Rao Makkena, Srivatsa Prativadibhayankaram +2
Reducing computational complexity remains a critical challenge for the widespread adoption of learning-based image compression techniques. In this work, we propose TreeNet, a novel…
Sliding Window Attention for Learned Video Compression
Alexander Kopte, André Kaup
To manage the complexity of transformers in video compression, local attention mechanisms are a practical necessity. The common approach of partitioning frames into patches, howeve…
LoC-LIC: Low Complexity Learned Image Coding Using Hierarchical Feature Transforms
Ayman A. Ameen, Thomas Richter, André Kaup
Current learned image compression models typically exhibit high complexity, which demands significant computational resources. To overcome these challenges, we propose an innovativ…
Compact Latent Representation for Image Compression (CLRIC)
Ayman A. Ameen, Thomas Richter, André Kaup
Current image compression models often require separate models for each quality level, making them resource-intensive in terms of both training and storage. To address these limita…