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Papers Motion Synthesis

“Motion Synthesis” 태그가 달린 논문 377편 · 필터 해제

Spatiotemporally Decoupled Autoregressive Diffusion Model for Human Motion Generation

2026-08-24 · Chengqun Yang, Liang Xu, Yanping Li, Fulong Liu 외 arxiv

Text-driven human motion synthesis has made substantial development with two core modules of motion representation and generative architecture. For representation, Vector Quantization (VQ)-based methods compress motion d…

Motion Synthesis

Natural Sit-to-Stand Motion Synthesis For Humanoids via Guided Assistance Curricula and Staged Rewards

2026-08-21 · Meet Pal Singh, Vyankatesh Ashtekar, Ashish Dutta arxiv

A humanoid has infinitely many ways to stand up from sitting while maintaining balance, making sit-to-stand (STS) a challenging control problem. We synthesise natural humanoid STS motion from scratch using reinforcement …

Reinforcement LearningMotion Synthesis

Learning to Beat: Phenotype-Guided Latent Flow with Regional Motion Priors for Biventricular Motion Synthesis

2026-08-20 · Xuan Yang, Xiaohan Yuan, Hao Li, Lingyu Chen 외 arxiv

Full-cycle biventricular geometry is essential for characterizing cardiac function. However, dense and temporally consistent 3D+t biventricular meshes are not routinely available, whereas end-diastolic (ED) anatomy can o…

Motion Synthesis

SparseCtrl-HOI: Sparse Temporal Control for Human-Object Interaction Video Generation

2026-07-07 · Shenbo Xie, Mingrui Cai, Xu Yang, Yifei Liu 외 arxiv

Human-Object Interaction (HOI) video generation aims to synthesize realistic videos of humans manipulating diverse objects, serving as a promising avenue for AI-driven live streaming e-commerce. A primary obstacle in thi…

Motion SynthesisVideo Generationhand-object pose

DeSeG: Decoupling Semantic Intent and Geometric Constraints for Physically Plausible Human-Scene Interaction

2026-07-07 · Jiakun Li, Zhe Li, Wenqiang Wu, Zheng Chang 외 arxiv

Synthesizing physically plausible human-scene interactions (HSI) remains a critical challenge in computer vision and the development of human avatars. Although recent generative models enable diverse motion synthesis, th…

Motion Synthesis

PRISM: Personalized Robotic Dataset Generation via Image-based Scene and Motion Synthesis

2026-07-06 · Dogyu Ko, Haneul Kim, Chanyoung Yeo, Dowoon Lee 외 arxiv

Recent advances in large-scale pretrained vision-language-action models have improved robot policy learning, but directly deploying such policies in user-specific environments remains challenging due to limited generaliz…

Motion Synthesis

PoseShield: Neural Collision Fields for Human Self-Collision Resolution

2026-06-29 · Zhengyuan Li, Zeyun Deng, Yifan Shen, Liangyan Gui 외 arxiv

Self-collision remains a persistent challenge in SMPL-based human pose estimation and motion generation. Under extreme articulations or stochastic motion synthesis, generated meshes frequently exhibit self-penetrations, …

Motion SynthesisPose Estimation

SICAGE: Speaker-Independent Culture-Aware Gesture Generation using TED4C-L Dataset

2026-06-29 · Ariel Gjaci, Antonio Sgorbissa, Vittorio Murino arxiv

Recent co-speech gesture generation methods often overlook cultural differences, limiting their effectiveness in human-agent interaction. Moreover, culture-conditioned models are rarely evaluated under speaker-disjoint s…

Domain GeneralizationGesture GenerationMotion Synthesis

In-Context Model Predictive Generation: Open-Vocabulary Motion Synthesis from Language Models to Physics

2026-06-25 · Xiaomeng Fu, Junfan Lin, Yang Liu, Yaowei Wang 외 arxiv

Synthesizing human motion from textual descriptions is essential for immersive digital applications, yet existing methods face a persistent trade-off between semantic fidelity and physical realism. Large language model (…

Motion Synthesis

Beyond MoCap: Scaling Motion Tokenizers with Synthetic Human Motion for Generative Modeling

2026-06-25 · Yiwen Yan, Wanning He, Yu-Wing Tai arxiv

Human motion generation models are fundamentally constrained by the limited diversity of motion capture datasets, which predominantly contain common, repetitive actions and fail to cover the long tail of complex human mo…

Representation LearningMotion Synthesis

Follow Your Track: Precise Skeleton Animation Controlled by 3D Trajectories

2026-06-24 · Yueting Liu, Yanqin Jiang, Nian Liu, Jingmen Zhou 외 arxiv

4D generation aims to animate 3D objects with realistic motion, holding great promise for applications. Existing methods typically decouple 3D asset generation from motion synthesis: acquire a 3D asset, prepare a structu…

Motion Synthesis

WOLF-VLA: Whole-Body Humanoid Optimal Locomotion Framework for Vision-Language-Action Learning

2026-06-24 · Melya Boukheddimi, Omar Adjali, Daniel Sontag, Frank Kirchner arxiv

Vision-Language-Action (VLA) models have recently demonstrated strong generalization in robotic manipulation, yet their applicability to whole-body, contact-rich humanoid locomotion remains severely underexplored due to …

Motion Synthesis

CP4D: Compositional Physics-aware 4D Scene Generation

2026-06-08 · Hanxin Zhu, Cong Wang, Tianyu He, Long Chen 외 arxiv

4D generation (\textit{i.e.}, dynamic 3D generation) has recently emerged as a rapidly growing research frontier due to its powerful spatiotemporal modeling capabilities. However, despite notable advances, existing appro…

Scene GenerationMotion Synthesis3D Generation

PhysAgent: Automating Physics-Based 4D Synthesis via Trajectory-Grounded Multi-Agent Feedback

2026-06-07 · Chunji Lv, Jiaxi Ye, Yuchen Jiang, Rexar Lin 외 arxiv

Achieving fully automated, physically plausible 3D motion synthesis is a core objective in graphics and generative AI. However, configuring complex environmental force fields still relies entirely on manual expert interv…

Motion Synthesis

MultiAct: Text-to-Motion Generation from Composite Text via Tailored Attention Guidance

2026-05-29 · Nathan Sala, Ofir Abramovich, Ariel Shamir, Daniel Cohen-Or 외 arxiv

Text-to-motion generation has progressed rapidly in recent years, offering an expressive interface for animation and human-computer interaction. However, current models remain brittle when handling prompts that describe …

Motion Synthesis

AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked Modeling

2026-05-28 · Yiheng Li, Zhuo Li, Ruibing Hou, Yingjie Chen 외 arxiv

Conditional human motion generation remains a fundamental challenge in computer vision and robotics. Despite significant progress, current methods are often constrained by fixed modality configurations and task-specific …

Motion Synthesis

Dex2HOI: Dexterous Bimanual Two-Object Interaction Generation

2026-05-28 · Chrysa Pratikaki, Pablo Ruiz-Ponce, Jiankang Deng, Stefanos Zafeiriou 외 arxiv

Recent advances in 4D Human-Object Interaction (HOI) generation have enabled increasingly realistic motion synthesis, particularly for single-object manipulation. Yet current research overlooks an inherent property of hu…

Motion Synthesis

Sketch2Motion: Text-driven 2D Sketch to 3D Animation via Diffusion-guided Skeleton Optimization

2026-05-27 · Gaurav Rai, Ojaswa Sharma arxiv

Animation of 2D hand-drawn sketches provides an effective medium for visual communication. However, these sketches pose challenges, particularly in handling occlusions and accurately mapping motion. While 3D animation na…

Motion Synthesis

Generative Animations: A Multi-Model Pipeline for Prompt-Driven Motion Synthesis

2026-05-26 · Mannat Khurana, Sanyam Jain, Rishav Agarwal arxiv

Animation elevates digital documents into immersive experiences, yet creating custom motion paths remains cumbersome, requiring designers to manually select presets, plot Bézier points, and configure timing properties. W…

Motion SynthesisVisual GroundingSemantic Parsing

RePCM: Region-Specific and Phenotype-Adaptive Bi-Ventricular Cardiac Motion Synthesis

2026-05-20 · Xuan Yang, Xiaohan Yuan, Hao Li, Lingyu Chen 외 arxiv

Cardiac motion over a cardiac cycle is crucial for quantifying regional function and is strongly affected by cardiovascular diseases. Since temporally dense mesh sequences are difficult to obtain in practice, we focus on…

Motion Synthesis
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