SOURCE-LINKED INTELLIGENCE
Efficient JPEG Restoration in the Wavelet Domain via Mean Flows
Latest JPEG restoration systems achieve strong quality with large models, yet often remain too slow and expensive for efficient on-device deployment. We present a 65M-parameter generative restorer that attains the lowest LPIPS at QF 10 and 20 on LIVE-1, Urban100, and DIV2K-val while sustaining 8.05 images/s at $1024\times1024$ on a single RTX 3090, roughly $4.9\times$ the reported throughput of one-step SODiff at one-twentieth of its parameters. Trained from scratch, the model replaces the learned VAE encoder-decoder with an exactly invertible two-level Haar transform, predicts a clean wavelet
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-28T17:34:27.000Z
First collected: 2026-09-21T08:02:06.831Z. This is not the publication date.