33 citations · 38 across the 12 of their papers we have counts for
12 papers
SceneConductor: 3D Scene Generation from a Single Image with Multi-Agent Orchestration
Jeonghwan Kim, Yushi Lan, Yongwei Chen +3
Generating complete 3D scenes from a single image requires inferring globally consistent geometry, object relationships, and environmental context from inherently ambiguous visual…
PnP-U3D: Plug-and-Play 3D Framework Bridging Autoregression and Diffusion for Unified Understanding and Generation
Yongwei Chen, Tianyi Wei, Yushi Lan +4
The rapid progress of large multimodal models has inspired efforts toward unified frameworks that couple understanding and generation. While such paradigms have shown remarkable su…
PI-Light: Physics-Inspired Diffusion for Full-Image Relighting
Zhexin Liang, Zhaoxi Chen, Yongwei Chen +3
Full-image relighting remains a challenging problem due to the difficulty of collecting large-scale structured paired data, the difficulty of maintaining physical plausibility, and…
ArtiLatent: Realistic Articulated 3D Object Generation via Structured Latents
Honghua Chen, Yushi Lan, Yongwei Chen +1
We propose ArtiLatent, a generative framework that synthesizes human-made 3D objects with fine-grained geometry, accurate articulation, and realistic appearance. Our approach joint…
FastMesh: Efficient Artistic Mesh Generation via Component Decoupling
Jeonghwan Kim, Yushi Lan, Armando Fortes +2
Recent mesh generation approaches typically tokenize triangle meshes into sequences of tokens and train autoregressive models to generate these tokens sequentially. Despite substan…
SAR3D: Autoregressive 3D Object Generation and Understanding via Multi-scale 3D VQVAE
Yongwei Chen, Yushi Lan, Shangchen Zhou +2
Autoregressive models have demonstrated remarkable success across various fields, from large language models (LLMs) to large multimodal models (LMMs) and 2D content generation, mov…
MvDrag3D: Drag-based Creative 3D Editing via Multi-view Generation-Reconstruction Priors
Honghua Chen, Yushi Lan, Yongwei Chen +2
Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Ex…
ComboVerse: Compositional 3D Assets Creation Using Spatially-Aware Diffusion Guidance
Yongwei Chen, Tengfei Wang, Tong Wu +3
Generating high-quality 3D assets from a given image is highly desirable in various applications such as AR/VR. Recent advances in single-image 3D generation explore feed-forward m…
TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition
Yongwei Chen, Rui Chen, Jiabao Lei +2
Creation of 3D content by stylization is a promising yet challenging problem in computer vision and graphics research. In this work, we focus on stylizing photorealistic appearance…
Quasi-Balanced Self-Training on Noise-Aware Synthesis of Object Point Clouds for Closing Domain Gap
Yongwei Chen, Zihao Wang, Longkun Zou +2
Semantic analyses of object point clouds are largely driven by releasing of benchmarking datasets, including synthetic ones whose instances are sampled from object CAD models. Howe…
Universality of parametric Coupling Flows over parametric diffeomorphisms
Junlong Lyu, Zhitang Chen, Chang Feng +5
Invertible neural networks based on Coupling Flows CFlows) have various applications such as image synthesis and data compression. The approximation universality for CFlows is of p…
Deep Optimized Priors for 3D Shape Modeling and Reconstruction
Mingyue Yang, Yuxin Wen, Weikai Chen +2
Many learning-based approaches have difficulty scaling to unseen data, as the generality of its learned prior is limited to the scale and variations of the training samples. This h…