Forget the parameter race. Google's TurboQuant research compresses AI memory by 6x with zero accuracy loss. It's not ...
Abstract: Learning-based image compression algorithms typically focus on designing encoding and decoding networks and improving the accuracy of entropy model estimation to enhance the rate-distortion ...
2025-05-20: This repo is released. Training consists of two stages. In the first stage, we train hyper-encoders. In the second stage, we fine-tune both hyper-encoders and OSCAR's UNet with LoRA.
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. // See https://llvm.org/LICENSE.txt for license information. // SPDX-License ...
Abstract: High Dynamic Range (HDR) images present unique challenges for Learned Image Compression (LIC) due to their complex domain distribution compared to Low Dynamic Range (LDR) images. In coding ...
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