activity
20232026
most citedPhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamics

5 citations · 14 across the 12 of their papers we have counts for

collaborators

13 papers

cs.RO2026

GRAIL: Generating Humanoid Loco-Manipulation from World Models

Tianyi Xie, Haotian Zhang, Jinhyung Park +17

Scaling humanoid loco-manipulation requires robot-compatible demonstrations across diverse objects, whole-body motions, and scene geometries, but teleoperation and motion capture a…

cs.CV2026

DressWild: Feed-Forward Pose-Agnostic Garment Sewing Pattern Generation from In-the-Wild Images

Zeng Tao, Ying Jiang, Yunuo Chen +7

Recent advances in garment pattern generation have shown promising progress. However, existing feed-forward methods struggle with diverse poses and viewpoints, while optimization-b…

cs.GR2025

AnimaMimic: Imitating 3D Animation from Video Priors

Tianyi Xie, Yunuo Chen, Yaowei Guo +5

Creating realistic 3D animation remains a time-consuming and expertise-dependent process, requiring manual rigging, keyframing, and fine-tuning of complex motions. Meanwhile, video…

cs.RO2025

GRIP: A General Robotic Incremental Potential Contact Simulation Dataset for Unified Deformable-Rigid Coupled Grasping

Siyu Ma, Wenxin Du, Chang Yu +7

Grasping is fundamental to robotic manipulation, and recent advances in large-scale grasping datasets have provided essential training data and evaluation benchmarks, accelerating…

cs.CV2025

Dress-1-to-3: Single Image to Simulation-Ready 3D Outfit with Diffusion Prior and Differentiable Physics

Xuan Li, Chang Yu, Wenxin Du +5

Recent advances in large models have significantly advanced image-to-3D reconstruction. However, the generated models are often fused into a single piece, limiting their applicabil…

cs.GR2025★ 1 cited

PhysAnimator: Physics-Guided Generative Cartoon Animation

Tianyi Xie, Yiwei Zhao, Ying Jiang +1

Creating hand-drawn animation sequences is labor-intensive and demands professional expertise. We introduce PhysAnimator, a novel approach for generating physically plausible meanw…

cs.CV2024

PhysMotion: Physics-Grounded Dynamics From a Single Image

Xiyang Tan, Ying Jiang, Xuan Li +4

We introduce PhysMotion, a novel framework that leverages principled physics-based simulations to guide intermediate 3D representations generated from a single image and input cond…

cs.CV2024★ 2 cited

VideoPhy: Evaluating Physical Commonsense for Video Generation

Hritik Bansal, Zongyu Lin, Tianyi Xie +7

Recent advances in internet-scale video data pretraining have led to the development of text-to-video generative models that can create high-quality videos across a broad range of…

cs.CV2024★ 1 cited

GarmentDreamer: 3DGS Guided Garment Synthesis with Diverse Geometry and Texture Details

Boqian Li, Xuan Li, Ying Jiang +5

Traditional 3D garment creation is labor-intensive, involving sketching, modeling, UV mapping, and texturing, which are time-consuming and costly. Recent advances in diffusion-base…

cs.LG2024★ 2 cited

Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication

Yunuo Chen, Tianyi Xie, Zeshun Zong +5

Existing diffusion-based text-to-3D generation methods primarily focus on producing visually realistic shapes and appearances, often neglecting the physical constraints necessary f…

cs.HC2024★ 2 cited

VR-GS: A Physical Dynamics-Aware Interactive Gaussian Splatting System in Virtual Reality

Ying Jiang, Chang Yu, Tianyi Xie +8

As consumer Virtual Reality (VR) and Mixed Reality (MR) technologies gain momentum, there's a growing focus on the development of engagements with 3D virtual content. Unfortunately…

cs.GR2023★ 5 cited

PhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamics

Tianyi Xie, Zeshun Zong, Yuxing Qiu +4

We introduce PhysGaussian, a new method that seamlessly integrates physically grounded Newtonian dynamics within 3D Gaussians to achieve high-quality novel motion synthesis. Employ…

cs.GR2023★ 1 cited

A Contact Proxy Splitting Method for Lagrangian Solid-Fluid Coupling

Tianyi Xie, Minchen Li, Yin Yang +1

We present a robust and efficient method for simulating Lagrangian solid-fluid coupling based on a new operator splitting strategy. We use variational formulations to approximate f…