Papers Motion Generation
“Motion Generation” 태그가 달린 논문 446편 · 필터 해제
SnapMoGen: Human Motion Generation from Expressive Texts
Text-to-motion generation has experienced remarkable progress in recent years. However, current approaches remain limited to synthesizing motion from short or general text prompts, primarily due to dataset constraints. T…
Motion GenerationGo to Zero: Towards Zero-shot Motion Generation with Million-scale Data
Generating diverse and natural human motion sequences based on textual descriptions constitutes a fundamental and challenging research area within the domains of computer vision, graphics, and robotics. Despite significa…
Motion GenerationZero-shot GeneralizationMotion Generation: A Survey of Generative Approaches and Benchmarks
Motion generation, the task of synthesizing realistic motion sequences from various conditioning inputs, has become a central problem in computer vision, computer graphics, and robotics, with applications ranging from an…
Motion GenerationSurveyA Unified Transformer-Based Framework with Pretraining For Whole Body Grasping Motion Generation
Accepted in the ICIP 2025 We present a novel transformer-based framework for whole-body grasping that addresses both pose generation and motion infilling, enabling realistic and stable object interactions. Our pipeline c…
Grasp GenerationMotion GenerationPlanMoGPT: Flow-Enhanced Progressive Planning for Text to Motion Synthesis
Recent advances in large language models (LLMs) have enabled breakthroughs in many multimodal generation tasks, but a significant performance gap still exists in text-to-motion generation, where LLM-based methods lag far…
DiversityMotion GenerationMotion Synthesismultimodal generationHuman-Centered Editable Speech-to-Sign-Language Generation via Streaming Conformer-Transformer and Resampling Hook
Existing end-to-end sign-language animation systems suffer from low naturalness, limited facial/body expressivity, and no user control. We propose a human-centered, real-time speech-to-sign animation framework that integ…
Motion GenerationText GenerationRL from Physical Feedback: Aligning Large Motion Models with Humanoid Control
This paper focuses on a critical challenge in robotics: translating text-driven human motions into executable actions for humanoid robots, enabling efficient and cost-effective learning of new behaviors. While existing t…
Humanoid ControlMotion GenerationSemantic correspondenceMotion-R1: Chain-of-Thought Reasoning and Reinforcement Learning for Human Motion Generation
Recent advances in large language models, especially in natural language understanding and reasoning, have opened new possibilities for text-to-motion generation. Although existing approaches have made notable progress i…
Language ModelingLanguage ModellingLogical ReasoningMotion Generation+2PhysiInter: Integrating Physical Mapping for High-Fidelity Human Interaction Generation
Driven by advancements in motion capture and generative artificial intelligence, leveraging large-scale MoCap datasets to train generative models for synthesizing diverse, realistic human motions has become a promising r…
Motion GenerationvalidSViMo: Synchronized Diffusion for Video and Motion Generation in Hand-object Interaction Scenarios
Hand-Object Interaction (HOI) generation has significant application potential. However, current 3D HOI motion generation approaches heavily rely on predefined 3D object models and lab-captured motion data, limiting gene…
Motion GenerationVideo GenerationUniConFlow: A Unified Constrained Generalization Framework for Certified Motion Planning with Flow Matching Models
Generative models have become increasingly powerful tools for robot motion generation, enabling flexible and multimodal trajectory generation across various tasks. Yet, most existing approaches remain limited in handling…
Collision AvoidanceMotion GenerationMotion PlanningCaptivity-Escape Games as a Means for Safety in Online Motion Generation
This paper presents a method that addresses the conservatism, computational effort, and limited numerical accuracy of existing frameworks and methods that ensure safety in online model-based motion generation, commonly r…
Motion GenerationMotion PlanningEPFL-Smart-Kitchen-30: Densely annotated cooking dataset with 3D kinematics to challenge video and language models
Understanding behavior requires datasets that capture humans while carrying out complex tasks. The kitchen is an excellent environment for assessing human motor and cognitive function, as many complex actions are natural…
Action RecognitionAction SegmentationMotion GenerationSemantics-Aware Human Motion Generation from Audio Instructions
Recent advances in interactive technologies have highlighted the prominence of audio signals for semantic encoding. This paper explores a new task, where audio signals are used as conditioning inputs to generate motions …
Motion GenerationWav2Sem: Plug-and-Play Audio Semantic Decoupling for 3D Speech-Driven Facial Animation
In 3D speech-driven facial animation generation, existing methods commonly employ pre-trained self-supervised audio models as encoders. However, due to the prevalence of phonetically similar syllables with distinct lip s…
Motion GenerationMMGT: Motion Mask Guided Two-Stage Network for Co-Speech Gesture Video Generation
Co-Speech Gesture Video Generation aims to generate vivid speech videos from audio-driven still images, which is challenging due to the diversity of different parts of the body in terms of amplitude of motion, audio rele…
Motion GenerationVideo GenerationFrom Motion to Behavior: Hierarchical Modeling of Humanoid Generative Behavior Control
Human motion generative modeling or synthesis aims to characterize complicated human motions of daily activities in diverse real-world environments. However, current research predominantly focuses on either low-level, sh…
Motion GenerationMotion PlanningTask and Motion PlanningIKMo: Image-Keyframed Motion Generation with Trajectory-Pose Conditioned Motion Diffusion Model
Existing human motion generation methods with trajectory and pose inputs operate global processing on both modalities, leading to suboptimal outputs. In this paper, we propose IKMo, an image-keyframed motion generation m…
Motion GenerationAbsolute Coordinates Make Motion Generation Easy
State-of-the-art text-to-motion generation models rely on the kinematic-aware, local-relative motion representation popularized by HumanML3D, which encodes motion relative to the pelvis and to the previous frame with bui…
Motion GenerationFrom Single Images to Motion Policies via Video-Generation Environment Representations
Autonomous robots typically need to construct representations of their surroundings and adapt their motions to the geometry of their environment. Here, we tackle the problem of constructing a policy model for collision-f…
Depth EstimationMonocular Depth EstimationMotion GenerationVideo Generation