22 citations · 30 across the 37 of their papers we have counts for
15 papers · 1 filter
Characterizing chordal -EPG graphs via admissible clique tree orientations
Bin Sun, Shou-Jun Xu, Yu Yang
A -bend path is a non-self-intersecting polyline that lies on a grid and consists of at most axis-parallel line segments. An -EPG graph is a graph whose vertice…
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…
Revisiting Spectral Representations in Generative Diffusion Models
Yuehao Wang, Peihao Wang, Hanwen Jiang +3
Diffusion models have shown remarkable performance on diverse generation tasks. Recent work finds that imposing representation alignment on the hidden states of diffusion networks…
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…
MeshFlow: Mesh Generation with Equivariant Flow Matching
Qi Sun, Kiyohiro Nakayama, Jing Nathan Yan +6
Meshes are among the most common 3D scene representations, but directly generating meshes is challenging because the representation contains important symmetries, including permuta…
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…
SECOND-Grasp: Semantic Contact-guided Dexterous Grasping
Han Yi Shin, Heeju Ko, Jaewon Mun +6
Achieving reliable robotic manipulation, such as dexterous grasping, requires a synergy between physically stable interactions and semantic task guidance, yet these objectives are…
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…