31 citations · 79 across the 19 of their papers we have counts for
20 papers
MegaParts: Scaling Part-Aware 3D Object Generation to 300 Parts via Token-Efficient Autoregressive Modeling
Manwen Liao, Xinyu Lian, Jian Mao +11
Part-aware 3D object generation is essential for graphics applications such as controllable modeling, editing, and articulation, where objects are represented as coherent assemblie…
InternScenes: A Large-scale Simulatable Indoor Scene Dataset with Realistic Layouts
Weipeng Zhong, Peizhou Cao, Yichen Jin +9
The advancement of Embodied AI heavily relies on large-scale, simulatable 3D scene datasets characterized by scene diversity and realistic layouts. However, existing datasets typic…
MeshCoder: LLM-Powered Structured Mesh Code Generation from Point Clouds
Bingquan Dai, Li Ray Luo, Qihong Tang +9
Reconstructing 3D objects into editable programs is pivotal for applications like reverse engineering and shape editing. However, existing methods often rely on limited domain-spec…
AnySplat: Feed-forward 3D Gaussian Splatting from Unconstrained Views
Lihan Jiang, Yucheng Mao, Linning Xu +9
We introduce AnySplat, a feed forward network for novel view synthesis from uncalibrated image collections. In contrast to traditional neural rendering pipelines that demand known…
Infinite Mobility: Scalable High-Fidelity Synthesis of Articulated Objects via Procedural Generation
Xinyu Lian, Zichao Yu, Ruiming Liang +9
Large-scale articulated objects with high quality are desperately needed for multiple tasks related to embodied AI. Most existing methods for creating articulated objects are eithe…
Boosting 3D Object Generation through PBR Materials
Yitong Wang, Xudong Xu, Li Ma +2
Automatic 3D content creation has gained increasing attention recently, due to its potential in various applications such as video games, film industry, and AR/VR. Recent advanceme…
RoomTex: Texturing Compositional Indoor Scenes via Iterative Inpainting
Qi Wang, Ruijie Lu, Xudong Xu +5
The advancement of diffusion models has pushed the boundary of text-to-3D object generation. While it is straightforward to composite objects into a scene with reasonable geometry,…
TELA: Text to Layer-wise 3D Clothed Human Generation
Junting Dong, Qi Fang, Zehuan Huang +4
This paper addresses the task of 3D clothed human generation from textural descriptions. Previous works usually encode the human body and clothes as a holistic model and generate t…
GetMesh: A Controllable Model for High-quality Mesh Generation and Manipulation
Zhaoyang Lyu, Ben Fei, Jinyi Wang +4
Mesh is a fundamental representation of 3D assets in various industrial applications, and is widely supported by professional softwares. However, due to its irregular structure, me…
DiffMorpher: Unleashing the Capability of Diffusion Models for Image Morphing
Kaiwen Zhang, Yifan Zhou, Xudong Xu +2
Diffusion models have achieved remarkable image generation quality surpassing previous generative models. However, a notable limitation of diffusion models, in comparison to GANs,…
MATLABER: Material-Aware Text-to-3D via LAtent BRDF auto-EncodeR
Xudong Xu, Zhaoyang Lyu, Xingang Pan +1
Based on powerful text-to-image diffusion models, text-to-3D generation has made significant progress in generating compelling geometry and appearance. However, existing methods st…
HyperStyle3D: Text-Guided 3D Portrait Stylization via Hypernetworks
Zhuo Chen, Xudong Xu, Yichao Yan +5
Portrait stylization is a long-standing task enabling extensive applications. Although 2D-based methods have made great progress in recent years, real-world applications such as me…
Voxurf: Voxel-based Efficient and Accurate Neural Surface Reconstruction
Tong Wu, Jiaqi Wang, Xingang Pan +4
Neural surface reconstruction aims to reconstruct accurate 3D surfaces based on multi-view images. Previous methods based on neural volume rendering mostly train a fully implicit m…
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion
Zhaoyang Lyu, Zhifeng Kong, Xudong Xu +2
3D point cloud is an important 3D representation for capturing real world 3D objects. However, real-scanned 3D point clouds are often incomplete, and it is important to recover com…
Generative Occupancy Fields for 3D Surface-Aware Image Synthesis
Xudong Xu, Xingang Pan, Dahua Lin +1
The advent of generative radiance fields has significantly promoted the development of 3D-aware image synthesis. The cumulative rendering process in radiance fields makes training…
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis
Xingang Pan, Xudong Xu, Chen Change Loy +2
The advancement of generative radiance fields has pushed the boundary of 3D-aware image synthesis. Motivated by the observation that a 3D object should look realistic from multiple…
Visually Informed Binaural Audio Generation without Binaural Audios
Xudong Xu, Hang Zhou, Ziwei Liu +3
Stereophonic audio, especially binaural audio, plays an essential role in immersive viewing environments. Recent research has explored generating visually guided stereophonic audio…
Sep-Stereo: Visually Guided Stereophonic Audio Generation by Associating Source Separation
Hang Zhou, Xudong Xu, Dahua Lin +2
Stereophonic audio is an indispensable ingredient to enhance human auditory experience. Recent research has explored the usage of visual information as guidance to generate binaura…
Vision-Infused Deep Audio Inpainting
Hang Zhou, Ziwei Liu, Xudong Xu +2
Multi-modality perception is essential to develop interactive intelligence. In this work, we consider a new task of visual information-infused audio inpainting, \ie synthesizing mi…
Recursive Visual Sound Separation Using Minus-Plus Net
Xudong Xu, Bo Dai, Dahua Lin
Sounds provide rich semantics, complementary to visual data, for many tasks. However, in practice, sounds from multiple sources are often mixed together. In this paper we propose a…