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Motion Generation

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Showing 301–325 of 446 papers

TitleStatusHype
Contact-aware Human Motion Generation from Textual Descriptions—0
ControlMM: Controllable Masked Motion Generation—0
Cooperative constrained motion coordination of networked heterogeneous vehicles—0
CoPAL: Corrective Planning of Robot Actions with Large Language Models—0
Co-Speech Gesture Video Generation with Implicit Motion-Audio Entanglement—0
Cross-Conditioned Recurrent Networks for Long-Term Synthesis of Inter-Person Human Motion Interactions—0
Cross-Modal Diffusion for Biomechanical Dynamical Systems Through Local Manifold Alignment—0
CrowdMoGen: Zero-Shot Text-Driven Collective Motion Generation—0
CustomListener: Text-guided Responsive Interaction for User-friendly Listening Head Generation—0
DanceFusion: A Spatio-Temporal Skeleton Diffusion Transformer for Audio-Driven Dance Motion Reconstruction—0
DanceMosaic: High-Fidelity Dance Generation with Multimodal Editability—0
DartControl: A Diffusion-Based Autoregressive Motion Model for Real-Time Text-Driven Motion Control—0
Deep Active Visual Attention for Real-time Robot Motion Generation: Emergence of Tool-body Assimilation and Adaptive Tool-use—0
Human-Centered Editable Speech-to-Sign-Language Generation via Streaming Conformer-Transformer and Resampling Hook—0
Deterministic-to-Stochastic Diverse Latent Feature Mapping for Human Motion Synthesis—0
Didn't see that coming: a survey on non-verbal social human behavior forecasting—0
DiffCollage: Parallel Generation of Large Content with Diffusion Models—0
DiffSHEG: A Diffusion-Based Approach for Real-Time Speech-driven Holistic 3D Expression and Gesture Generation—0
Diffuse-CLoC: Guided Diffusion for Physics-based Character Look-ahead Control—0
Diffusion-based Realistic Listening Head Generation via Hybrid Motion Modeling—0
Diffusion Implicit Policy for Unpaired Scene-aware Motion Synthesis—0
DiffusionPhase: Motion Diffusion in Frequency Domain—0
Digital Life Project: Autonomous 3D Characters with Social Intelligence—0
Direct Post-Training Preference Alignment for Multi-Agent Motion Generation Models Using Implicit Feedback from Pre-training Demonstrations—0
Discovery and recognition of motion primitives in human activities—0
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