265 citations · 785 across the 88 of their papers we have counts for
112 papers
PiHand: Latent Hand-Object Interaction Priors for Physics-Based Policy Learning
Niklas Berndt, Xianghui Xie, Enes Duran +2
Synthesizing physically grounded dexterous hand-object interactions is important for VR/AR, gaming, and robotics, yet remains challenging because subtle contact dynamics, diverse o…
COSMI: COmpositional Synthesis of Multi-object Interactions
Daniel Eskandar, Ilya A. Petrov, Gerard Pons-Moll
Generative models of human-object interaction are bounded by the data that exists: everyday activities involve several objects, but most captured datasets record one at a time, as…
PAMI: Part Anchored Motion for Text to Human-Object Interaction Generation
Chuqiao Li, Xianghui Xie, Yong Cao +2
Text-conditioned full-body human-object interaction (HOI) generation requires synthesizing human motion and object trajectories that match the input text while remaining precisely…
Revisiting Avatar-As-Image: High-Fidelity Registration is All You Need
Margaret Kostyrko, Yuxuan Xue, Garvita Tiwari +1
The representation of 3D clothed humans as standardized 2D UV texture and displacement maps over an underlying body model has long been studied. This compact representation is enti…
Ordered Diffusion for 3D Human Registration
Mattia Masiero, Ilya A. Petrov, Daniel Cremers +2
3D human registration has historically been treated as a regression task, assuming a unique ground-truth alignment exists between the template and an input point cloud. In reality,…
Head Avatars with Dynamic Explicit Hair
Vanessa Sklyarova, Haonan Chen, Berna Kabadayi +8
We present DynHair, a novel method for tracking and modeling dynamic hair for human head avatars. From video input, we reconstruct a dynamic head avatar with an explicit strand-bas…
SAMoR: Motion Modelling for Articulated Objects of Any Skeleton and Topology
Yuhao Zhang, Gerard Pons-Moll, Tolga Birdal
Modeling motion for articulated objects of arbitrary skeleton topology remains difficult: existing motion generators target a fixed human skeleton, and prior adaptations either fai…
Stitched Embeddings: A Unified Latent Space for 3D Garments and 2D Patterns
Andrea Sanchietti, Riccardo Marin, Bharat Lal Bhatnagar +2
While garments are essential for realistic digital humans, their topological variety makes them much harder to model than parametric bodies. Traditional tailoring relies on 2D sewi…
RAGA: Real Time Ray Traced Gaussian Shadow Casting for 3DGS Avatar-Scene Interaction
Aymen Mir, Riza Alp Guler, Jian Wang +3
We study the problem of physically plausible shadow casting when animating 3D Gaussian Splatting (3DGS) avatars, either individually or in multi-avatar and object-interaction scena…
NextMotionQA: Benchmarking and Judging Human Motion Understanding with Vision-Language Models
Yong Cao, Chuqiao Li, Xianghui Xie +2
Reliable evaluation of human motion understanding is fundamental to advancing embodied AI, robotics, and animation. However, existing benchmarks suffer from coarse semantic granula…
InHabit: Leveraging Image Foundation Models for Scalable 3D Human Placement
Nikita Kister, Pradyumna YM, István Sárándi +3
Training embodied agents to understand 3D scenes as humans do requires large-scale data of people meaningfully interacting with diverse environments, yet such data is scarce. Real-…
DAMA: Disentangled Body-Anchored Gaussians for Controllable Multi-Layered Avatars
Daniel Eskandar, Berna Kabadayi, Garvita Tiwari +1
Existing 3D clothed avatar reconstruction methods achieve high visual fidelity but ignore geometric structure and physical plausibility. They either model clothed humans as a singl…
Learn2Splat: Extending the Horizon of Learned 3DGS Optimization
Naama Pearl, Stefano Esposito, Haofei Xu +6
3D Gaussian Splatting (3DGS) optimization is most commonly performed using general-purpose first-order optimizers such as Adam or SGD. Although robust across scenes, they update ea…
GeoRelight: Learning Joint Geometrical Relighting and Reconstruction with Flexible Multi-Modal Diffusion Transformers
Yuxuan Xue, Ruofan Liang, Egor Zakharov +6
Relighting a person from a single photo is an attractive but ill-posed task, as a 2D image ambiguously entangles 3D geometry, intrinsic appearance, and illumination. Current method…
PhysHead: Simulation-Ready Gaussian Head Avatars
Berna Kabadayi, Vanessa Sklyarova, Wojciech Zielonka +2
Realistic digital avatars require expressive and dynamic hair motion; however, most existing head avatar methods assume rigid hair movement. These methods often fail to disentangle…
GRAFT: Geometric Refinement and Fitting Transformer for Human Scene Reconstruction
Pradyumna YM, Yuxuan Xue, Yue Chen +3
Reconstructing physically plausible 3D human-scene interactions (HSI) from a single image currently presents a trade-off: optimization based methods offer accurate contact but are…
ActionPlan: Future-Aware Streaming Motion Synthesis via Frame-Level Action Planning
Eric Nazarenus, Chuqiao Li, Yannan He +3
We present ActionPlan, a unified motion diffusion framework that bridges real-time streaming with high-quality offline generation within a single model. The core idea is to introdu…
Hoi3DGen: Generating High-Quality Human-Object-Interactions in 3D
Agniv Sharma, Xianghui Xie, Tom Fischer +2
Modeling and generating 3D human-object interactions from text is crucial for applications in AR, XR, and gaming. Existing approaches often rely on score distillation from text-to-…
AHOY! Animatable Humans under Occlusion from YouTube Videos with Gaussian Splatting and Video Diffusion Priors
Aymen Mir, Riza Alp Guler, Xiangjun Tang +2
We present AHOY, a method for reconstructing complete, animatable 3D Gaussian avatars from in-the-wild monocular video despite heavy occlusion. Existing methods assume unoccluded i…
CLUTCH: Contextualized Language model for Unlocking Text-Conditioned Hand motion modelling in the wild
Balamurugan Thambiraja, Omid Taheri, Radek Danecek +3
Hands play a central role in daily life, yet modeling natural hand motions remains underexplored. Existing methods that tackle text-to-hand-motion generation or hand animation capt…
FrankenMotion: Part-level Human Motion Generation and Composition
Chuqiao Li, Xianghui Xie, Yong Cao +2
Human motion generation from text prompts has made remarkable progress in recent years. However, existing methods primarily rely on either sequence-level or action-level descriptio…
ELITE: Efficient Gaussian Head Avatar from a Monocular Video via Learned Initialization and TEst-time Generative Adaptation
Kim Youwang, Lee Hyoseok, Subin Park +2
We introduce ELITE, an Efficient Gaussian head avatar synthesis from a monocular video via Learned Initialization and TEst-time generative adaptation. Prior works rely either on a…
Animated 3DGS Avatars in Diverse Scenes with Consistent Lighting and Shadows
Aymen Mir, Riza Alp Guler, Jian Wang +2
We present a method for consistent lighting and shadows when animated 3D Gaussian Splatting (3DGS) avatars interact with 3DGS scenes or with dynamic objects inserted into otherwise…
MoLingo: Motion-Language Alignment for Text-to-Human Motion Generation
Yannan He, Garvita Tiwari, Xiaohan Zhang +4
We introduce MoLingo, a text-to-motion (T2M) model that generates realistic, lifelike human motion by denoising in a continuous latent space. Recent works perform latent space diff…