5 papers
OP4KSR: One-Step Patch-Free 4K Super-Resolution with Periodic Artifact Suppression
Chengyan Deng, Pengbin Yu, Zhentao Chen +6
Diffusion-based real-world image super-resolution (Real-ISR) has achieved remarkable perceptual quality; however, directly super-resolving images to 4K remains limited by extreme m…
UniCSG: Unified High-Fidelity Content-Constrained Style-Driven Generation via Staged Semantic and Frequency Disentanglement
Jingwei Yang, Ruoxi Wu, Wei Shen +4
Style transfer must match a target style while preserving content semantics. DiT-based diffusion models often suffer from content-style entanglement, leading to reference-content l…
Towards In-Context Tone Style Transfer with A Large-Scale Triplet Dataset
Yuhai Deng, Huimin She, Wei Shen +4
Tone style transfer for photo retouching aims to adapt the stylistic tone of the reference image to a given content image. However, the lack of high-quality large-scale triplet dat…
RefReward-SR: LR-Conditioned Reward Modeling for Preference-Aligned Super-Resolution
Yushuai Song, Weize Quan, Weining Wang +8
Recent advances in generative super-resolution (SR) have greatly improved visual realism, yet existing evaluation and optimization frameworks remain misaligned with human perceptio…
Block and Detail: Scaffolding Sketch-to-Image Generation
Vishnu Sarukkai, Lu Yuan, Mia Tang +2
We introduce a novel sketch-to-image tool that aligns with the iterative refinement process of artists. Our tool lets users sketch blocking strokes to coarsely represent the placem…