4 papers
Scale Where It Matters: Training-Free Localized Scaling for Diffusion Models
Qin Ren, Yufei Wang, Lanqing Guo +3
Diffusion models have become the dominant paradigm in text-to-image generation, and test-time scaling (TTS) improves sample quality by allocating additional computation at inferenc…
Mastering Regional 3DGS: Locating, Initializing, and Editing with Diverse 2D Priors
Lanqing Guo, Yufei Wang, Hezhen Hu +4
Many 3D scene editing tasks focus on modifying local regions rather than the entire scene, except for some global applications like style transfer, and in the context of 3D Gaussia…
Demystifying the Visual Quality Paradox in Multimodal Large Language Models
Shuo Xing, Lanqing Guo, Hongyuan Hua +5
Recent Multimodal Large Language Models (MLLMs) excel on benchmark vision-language tasks, yet little is known about how input visual quality shapes their responses. Does higher per…
GuideSR: Rethinking Guidance for One-Step High-Fidelity Diffusion-Based Super-Resolution
Aditya Arora, Zhengzhong Tu, Yufei Wang +3
In this paper, we propose GuideSR, a novel single-step diffusion-based image super-resolution (SR) model specifically designed to enhance image fidelity. Existing diffusion-based S…