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Evaluation Protocol.We construct an evaluation set of 1,000 images by randomly selecting one image per class from the ImageNet validation set

With a batch size of 16, learning rate of 10−4, we first train with L1, LPIPS losses for 200k steps, then incorporate PatchGAN adversarial loss for an additional100k steps · 2020

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CoD-Lite: Real-Time Diffusion-Based Generative Image Compression

cs.CV · 2026-04-14 · unverdicted · novelty 6.0

CoD-Lite delivers real-time generative image compression via a lightweight convolution-based diffusion codec with compression-oriented pre-training and distillation, achieving substantial bitrate savings.

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  • CoD-Lite: Real-Time Diffusion-Based Generative Image Compression cs.CV · 2026-04-14 · unverdicted · none · ref 16

    CoD-Lite delivers real-time generative image compression via a lightweight convolution-based diffusion codec with compression-oriented pre-training and distillation, achieving substantial bitrate savings.