CoCliCo: Extremely Low Bitrate Image Compression Based on CLIP Semantic and Tiny Color Map

Coding algorithms are usually designed to pixel-wisely reconstruct images, which limits the expected gains in terms of compression. In this work, we introduce a semantic compressed representation for images: CoCliCo. We encode the inputs into a CLIP latent vector and a tiny color map, and we use a conditional diffusion model for reconstruction. When compared to the most recent traditional and generative coders, our approach reaches drastic compression gains while keeping most of the high-level information and a good level of realism.