22 citations · 30 across the 37 of their papers we have counts for
36 papers · 1 filter
StableGrasp: Reconstructing Physically Stable Human Hand Grasps from Single Images
Han Jiang, Etienne Vouga, Qixing Huang +1
Reconstructing a physically stable human grasp from a single RGB image is challenging because physically modeling grasps is itself difficult, and the problem requires estimating no…
Instruction-Based Video Editing by Repurposing an Image Editing Model
Yunpeng Bai, Yossi Gandelsman, Michaël Gharbi +1
Instruction-based video editing is commonly built on video-pretrained generative backbones: a video diffusion transformer is adapted, at considerable cost, to condition on a source…
PE-Field 4D: Video Generation Models as Canvas
Yunpeng Bai, Haoxiang Li, Qixing Huang
Diffusion Transformers have recently achieved strong performance in video generation, yet controlling scene geometry under viewpoint changes and camera motion remains challenging.…
GenSP: Consistent Spherical Parameterization via Learning Shape Generative Models
Sai Karthikey Pentapati, Shashank Gupta, Rajesh Sureddi +3
We introduce GenSP, a data-driven framework that learns consistent spherical parameterizations across a collection of genus-0 shapes. Instead of optimizing the parameterization of…
ARAPDiffusion: Geometry-Distribution Feedback for Deformable 3D Shape Generation
Haibo Liu, Jinghan Ke, Haitao Yang +3
Deformable 3D shapes can undergo large changes in pose and morphology while still preserving plausible local geometry, yet generative models often produce samples with unnatural st…
Recovering Physically Plausible Human-Object Interactions from Monocular Videos
Dingbang Huang, Etienne Vouga, Qixing Huang +1
In this paper, we propose RePHO, a method to reconstruct physically plausible human-object interactions (HOI) from monocular videos. While existing kinematic-based approaches produ…
Mining Attribute Subspaces for Efficient Fine-tuning of 3D Foundation Models
Yu Jiang, Hanwen Jiang, Ahmed Abdelkader +4
With the emergence of 3D foundation models, there is growing interest in fine-tuning them for downstream tasks, where LoRA is the dominant fine-tuning paradigm. As 3D datasets exhi…
Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion
Zhenggang Tang, Yuehao Wang, Yuchen Fan +9
Recent text-to-scene generation approaches largely reduced the manual efforts required to create 3D scenes. However, their focus is either to generate a scene layout or to generate…
Information-Regularized Constrained Inversion for Stable Avatar Editing from Sparse Supervision
Zhenxiao Liang, Qixing Huang
Editing animatable human avatars typically relies on sparse supervision, often a few edited keyframes, yet naively fitting a reconstructed avatar to these edits frequently causes i…
Learning Convex Decomposition via Feature Fields
Yuezhi Yang, Qixing Huang, Mikaela Angelina Uy +1
This work proposes a new formulation to the long-standing problem of convex decomposition through learning feature fields, enabling the first feed-forward model for open-world conv…
ShapeGaussian: High-Fidelity 4D Human Reconstruction in Monocular Videos via Vision Priors
Zhenxiao Liang, Ning Zhang, Youbao Tang +4
We introduce ShapeGaussian, a high-fidelity, template-free method for 4D human reconstruction from casual monocular videos. Generic reconstruction methods lacking robust vision pri…
LiteGE: Lightweight Geodesic Embedding for Efficient Geodesics Computation and Non-Isometric Shape Correspondence
Yohanes Yudhi Adikusuma, Qixing Huang, Ying He
Computing geodesic distances on 3D surfaces is fundamental to many tasks in 3D vision and geometry processing, with deep connections to tasks such as shape correspondence. Recent l…
WorldReel: 4D Video Generation with Consistent Geometry and Motion Modeling
Shaoheng Fang, Hanwen Jiang, Yunpeng Bai +2
Recent video generators achieve striking photorealism, yet remain fundamentally inconsistent in 3D. We present WorldReel, a 4D video generator that is natively spatio-temporally co…
MVRoom: Controllable 3D Indoor Scene Generation with Multi-View Diffusion Models
Shaoheng Fang, Chaohui Yu, Fan Wang +1
We introduce MVRoom, a controllable novel view synthesis (NVS) pipeline for 3D indoor scenes that uses multi-view diffusion conditioned on a coarse 3D layout. MVRoom employs a two-…
GeoVideo: Introducing Geometric Regularization into Video Generation Model
Yunpeng Bai, Shaoheng Fang, Chaohui Yu +2
Recent advances in video generation have enabled the synthesis of high-quality and visually realistic clips using diffusion transformer models. However, most existing approaches op…
Decoupled Generative Modeling for Human-Object Interaction Synthesis
Hwanhee Jung, Seunggwan Lee, Jeongyoon Yoon +4
Synthesizing realistic human-object interaction (HOI) is essential for 3D computer vision and robotics, underpinning animation and embodied control. Existing approaches often requi…
Positional Encoding Field
Yunpeng Bai, Haoxiang Li, Qixing Huang
Diffusion Transformers (DiTs) have emerged as the dominant architecture for visual generation, powering state-of-the-art image and video models. By representing images as patch tok…
RayZer: A Self-supervised Large View Synthesis Model
Hanwen Jiang, Hao Tan, Peng Wang +8
We present RayZer, a self-supervised multi-view 3D Vision model trained without any 3D supervision, i.e., camera poses and scene geometry, while exhibiting emerging 3D awareness. C…
CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images
Cheng Chen, Jiacheng Wei, Tianrun Chen +8
Creating CAD digital twins from the physical world is crucial for manufacturing, design, and simulation. However, current methods typically rely on costly 3D scanning with labor-in…
HUMOTO: A 4D Dataset of Mocap Human Object Interactions
Jiaxin Lu, Chun-Hao Paul Huang, Uttaran Bhattacharya +2
We present Human Motions with Objects (HUMOTO), a high-fidelity dataset of human-object interactions for motion generation, computer vision, and robotics applications. Featuring 73…
Reconstructing Humans with a Biomechanically Accurate Skeleton
Yan Xia, Xiaowei Zhou, Etienne Vouga +2
In this paper, we introduce a method for reconstructing 3D humans from a single image using a biomechanically accurate skeleton model. To achieve this, we train a transformer that…
PASTA: Part-Aware Sketch-to-3D Shape Generation with Text-Aligned Prior
Seunggwan Lee, Hwanhee Jung, Byoungsoo Koh +3
A fundamental challenge in conditional 3D shape generation is to minimize the information loss and maximize the intention of user input. Existing approaches have predominantly focu…
Escaping Plato's Cave: Towards the Alignment of 3D and Text Latent Spaces
Souhail Hadgi, Luca Moschella, Andrea Santilli +5
Recent works have shown that, when trained at scale, uni-modal 2D vision and text encoders converge to learned features that share remarkable structural properties, despite arising…
MegaSynth: Scaling Up 3D Scene Reconstruction with Synthesized Data
Hanwen Jiang, Zexiang Xu, Desai Xie +11
We propose scaling up 3D scene reconstruction by training with synthesized data. At the core of our work is MegaSynth, a procedurally generated 3D dataset comprising 700K scenes -…