2 citations · 3 across the 5 of their papers we have counts for
7 papers · 1 filter
3DGen-Bench: Comprehensive Benchmark Suite for 3D Generative Models
Yuhan Zhang, Mengchen Zhang, Tong Wu +4
3D generation is experiencing rapid advancements, while the development of 3D evaluation has not kept pace. How to keep automatic evaluation equitably aligned with human perception…
Neural LightRig: Unlocking Accurate Object Normal and Material Estimation with Multi-Light Diffusion
Zexin He, Tengfei Wang, Xin Huang +2
Recovering the geometry and materials of objects from a single image is challenging due to its under-constrained nature. In this paper, we present Neural LightRig, a novel framewor…
Material Anything: Generating Materials for Any 3D Object via Diffusion
Xin Huang, Tengfei Wang, Ziwei Liu +1
We present Material Anything, a fully-automated, unified diffusion framework designed to generate physically-based materials for 3D objects. Unlike existing methods that rely on co…
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Zhenwei Wang, Tengfei Wang, Zexin He +3
In 3D modeling, designers often use an existing 3D model as a reference to create new ones. This practice has inspired the development of Phidias, a novel generative model that use…
Omni6D: Large-Vocabulary 3D Object Dataset for Category-Level 6D Object Pose Estimation
Mengchen Zhang, Tong Wu, Tai Wang +3
6D object pose estimation aims at determining an object's translation, rotation, and scale, typically from a single RGBD image. Recent advancements have expanded this estimation fr…
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…