56 citations · 96 across the 11 of their papers we have counts for
11 papers
LightMover: Generative Light Movement with Color and Intensity Controls
Gengze Zhou, Tianyu Wang, Soo Ye Kim +7
We present LightMover, a framework for controllable light manipulation in single images that leverages video diffusion priors to produce physically plausible illumination changes w…
TEXGen: a Generative Diffusion Model for Mesh Textures
Xin Yu, Ze Yuan, Yuan-Chen Guo +6
While high-quality texture maps are essential for realistic 3D asset rendering, few studies have explored learning directly in the texture space, especially on large-scale datasets…
GO-NeRF: Generating Objects in Neural Radiance Fields for Virtual Reality Content Creation
Peng Dai, Feitong Tan, Xin Yu +3
Virtual environments (VEs) are pivotal for virtual, augmented, and mixed reality systems. Despite advances in 3D generation and reconstruction, the direct creation of 3D objects wi…
UniDream: Unifying Diffusion Priors for Relightable Text-to-3D Generation
Zexiang Liu, Yangguang Li, Youtian Lin +7
Recent advancements in text-to-3D generation technology have significantly advanced the conversion of textual descriptions into imaginative well-geometrical and finely textured 3D…
Text-to-3D with Classifier Score Distillation
Xin Yu, Yuan-Chen Guo, Yangguang Li +3
Text-to-3D generation has made remarkable progress recently, particularly with methods based on Score Distillation Sampling (SDS) that leverages pre-trained 2D diffusion models. Wh…
Texture Generation on 3D Meshes with Point-UV Diffusion
Xin Yu, Peng Dai, Wenbo Li +3
In this work, we focus on synthesizing high-quality textures on 3D meshes. We present Point-UV diffusion, a coarse-to-fine pipeline that marries the denoising diffusion model with…
Hybrid Neural Rendering for Large-Scale Scenes with Motion Blur
Peng Dai, Yinda Zhang, Xin Yu +2
Rendering novel view images is highly desirable for many applications. Despite recent progress, it remains challenging to render high-fidelity and view-consistent novel views of la…
Image Inpainting via Iteratively Decoupled Probabilistic Modeling
Wenbo Li, Xin Yu, Kun Zhou +3
Generative adversarial networks (GANs) have made great success in image inpainting yet still have difficulties tackling large missing regions. In contrast, iterative probabilistic…
Is synthetic data from generative models ready for image recognition?
Ruifei He, Shuyang Sun, Xin Yu +5
Recent text-to-image generation models have shown promising results in generating high-fidelity photo-realistic images. Though the results are astonishing to human eyes, how applic…
Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing
Xin Yu, Peng Dai, Wenbo Li +4
With the rapid development of mobile devices, modern widely-used mobile phones typically allow users to capture 4K resolution (i.e., ultra-high-definition) images. However, for ima…
Video Demoireing with Relation-Based Temporal Consistency
Peng Dai, Xin Yu, Lan Ma +5
Moire patterns, appearing as color distortions, severely degrade image and video qualities when filming a screen with digital cameras. Considering the increasing demands for captur…