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cs.CV2026

LPM: Industrial-Scale Generative Video Restoration

Bichuan Zhu, Fulin Li, Jiachao Gong +14

We present the Large Processing Model (LPM), a diffusion-based generative framework for photorealistic video restoration under complex, in-the-wild degradations. To our knowledge,…

cs.CV2026

You Don't Need All That Attention: Surgical Memorization Mitigation in Text-to-Image Diffusion Models

Kairan Zhao, Eleni Triantafillou, Peter Triantafillou

Generative models have been shown to "memorize" certain training data, leading to verbatim or near-verbatim generating images, which may cause privacy concerns or copyright infring…

cs.CV2025

Visual Autoregressive Modeling for Image Super-Resolution

Yunpeng Qu, Kun Yuan, Jinhua Hao +4

Image Super-Resolution (ISR) has seen significant progress with the introduction of remarkable generative models. However, challenges such as the trade-off issues between fidelity…

cs.CV20243 cited

CasSR: Activating Image Power for Real-World Image Super-Resolution

Haolan Chen, Jinhua Hao, Kai Zhao +4

The objective of image super-resolution is to generate clean and high-resolution images from degraded versions. Recent advancements in diffusion modeling have led to the emergence…

cs.CV2024

XPSR: Cross-modal Priors for Diffusion-based Image Super-Resolution

Yunpeng Qu, Kun Yuan, Kai Zhao +4

Diffusion-based methods, endowed with a formidable generative prior, have received increasing attention in Image Super-Resolution (ISR) recently. However, as low-resolution (LR) im…