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Semantics Disentanglement and Composition for Versatile Codec toward both Human-eye Perception and Machine Vision Task
While learned image compression methods have achieved impressive results in either human visual perception or machine vision tasks, they are often specialized only for one domain.
Tell Codec What Worth Compressing: Semantically Disentangled Image Coding for Machine with LMMs
We present a new image compression paradigm to achieve ``intelligently coding for machine'' by cleverly leveraging the common sense of Large Multimodal Models (LMMs).
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