1 citations · 2 across the 17 of their papers we have counts for
6 papers · 1 filter
MaskCRT: Masked Conditional Residual Transformer for Learned Video Compression
Yi-Hsin Chen, Hong-Sheng Xie, Cheng-Wei Chen +4
Conditional coding has lately emerged as the mainstream approach to learned video compression. However, a recent study shows that it may perform worse than residual coding when the…
Transformer-based Image Compression with Variable Image Quality Objectives
Chia-Hao Kao, Yi-Hsin Chen, Cheng Chien +2
This paper presents a Transformer-based image compression system that allows for a variable image quality objective according to the user's preference. Optimizing a learned codec f…
MoTIF: Learning Motion Trajectories with Local Implicit Neural Functions for Continuous Space-Time Video Super-Resolution
Yi-Hsin Chen, Si-Cun Chen, Yen-Yu Lin +1
This work addresses continuous space-time video super-resolution (C-STVSR) that aims to up-scale an input video both spatially and temporally by any scaling factors. One key challe…
TransTIC: Transferring Transformer-based Image Compression from Human Perception to Machine Perception
Yi-Hsin Chen, Ying-Chieh Weng, Chia-Hao Kao +3
This work aims for transferring a Transformer-based image compression codec from human perception to machine perception without fine-tuning the codec. We propose a transferable Tra…
Transformer-based Variable-rate Image Compression with Region-of-interest Control
Chia-Hao Kao, Ying-Chieh Weng, Yi-Hsin Chen +2
This paper proposes a transformer-based learned image compression system. It is capable of achieving variable-rate compression with a single model while supporting the region-of-in…
Content-Adaptive Motion Rate Adaption for Learned Video Compression
Chih-Hsuan Lin, Yi-Hsin Chen, Wen-Hsiao Peng
This paper introduces an online motion rate adaptation scheme for learned video compression, with the aim of achieving content-adaptive coding on individual test sequences to mitig…