TLIC: Learned Image Compression with ROI-Weighted Distortion and Bit Allocation
arXiv:2401.08154v31 citations
AI Analysis
This addresses image compression for applications needing enhanced visual fidelity, but it appears incremental as it builds on existing methods with specific tweaks.
The paper tackles image compression by using adversarial loss for realistic textures and ROI masks to guide bit allocation, resulting in improved perceptual quality.
This short paper describes our method for the track of image compression. To achieve better perceptual quality, we use the adversarial loss to generate realistic textures, use region of interest (ROI) mask to guide the bit allocation for different regions. Our Team name is TLIC.