6 papers · 1 filter
Allo{SR}: Rectifying One-Step Super-Resolution to Stay Real via Allomorphic Generative Flows
Zihan Wang, Xudong Huang, Junbo Qiao +4
Real-world image super-resolution (Real-SR) has been revolutionized by leveraging the powerful generative priors from Diffusion Models (DMs) and Flow Matching (FM). However, existi…
MEPA: Multi-Scale Representation Alignment for Visual Autoregressive Modeling with Mixture of Experts
Nuoyan Zhou, Zhijun Tu, Lei Yu +4
Visual AutoRegressive modeling (VAR) has pioneered a coarse-to-fine multi-scale autoregressive generative paradigm, demonstrating strong capabilities in image generation. However,…
CSD: Content-aware Speculative Decoding for Efficient Image Generation
Mingcheng Wang, Junbo Qiao, Yunchen Li +8
Speculative decoding (SD) has emerged as a key solution to accelerate the inference of autoregressive models. However, in the field of image generation, it faces the challenge of l…
RealSR-R1: Reinforcement Learning for Real-World Image Super-Resolution with Vision-Language Chain-of-Thought
Junbo Qiao, Miaomiao Cai, Wei Li +5
Real-World Image Super-Resolution is one of the most challenging task in image restoration. However, existing methods struggle with an accurate understanding of degraded image cont…
From Sequential to Spatial: Reordering Autoregression for Efficient Visual Generation
Siyang Wang, Hanting Li, Wei Li +3
Inspired by the remarkable success of autoregressive models in language modeling, this paradigm has been widely adopted in visual generation. However, the sequential token-by-token…
Beyond Textual CoT: Interleaved Text-Image Chains with Deep Confidence Reasoning for Image Editing
Zhentao Zou, Zhengrong Yue, Kunpeng Du +9
Image editing with natural language has gained significant popularity, yet existing methods struggle with intricate object intersections and fine-grained spatial relationships due…