Motion Synthesis
90 papers with code • 9 benchmarks • 13 datasets
Benchmarks
These leaderboards are used to track progress in Motion Synthesis
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Datasets
HumanML3D
KIT Motion-Language
HumanAct12
AIST++
InterHuman
BRACE
LaFAN1
CHAIRS dataset
Latest papers with no code
Motion Flow Matching for Human Motion Synthesis and Editing
In this paper, we propose \emph{Motion Flow Matching}, a novel generative model designed for human motion generation featuring efficient sampling and effectiveness in motion editing applications.
Digital Life Project: Autonomous 3D Characters with Social Intelligence
In this work, we present Digital Life Project, a framework utilizing language as the universal medium to build autonomous 3D characters, who are capable of engaging in social interactions and expressing with articulated body motions, thereby simulating life in a digital environment.
EMDM: Efficient Motion Diffusion Model for Fast and High-Quality Motion Generation
We introduce Efficient Motion Diffusion Model (EMDM) for fast and high-quality human motion generation.
AAMDM: Accelerated Auto-regressive Motion Diffusion Model
This paper introduces the Accelerated Auto-regressive Motion Diffusion Model (AAMDM), a novel motion synthesis framework designed to achieve quality, diversity, and efficiency all together.
OmniMotionGPT: Animal Motion Generation with Limited Data
Our paper aims to generate diverse and realistic animal motion sequences from textual descriptions, without a large-scale animal text-motion dataset.
Probabilistic Speech-Driven 3D Facial Motion Synthesis: New Benchmarks, Methods, and Applications
While these models can achieve high-quality lip articulation for speakers in the training set, they are unable to capture the full and diverse distribution of 3D facial motions that accompany speech in the real world.
ReMoS: 3D Motion-Conditioned Reaction Synthesis for Two-Person Interactions
Current approaches for 3D human motion synthesis generate high-quality animations of digital humans performing a wide variety of actions and gestures.
A Unified Framework for Multimodal, Multi-Part Human Motion Synthesis
The field has made significant progress in synthesizing realistic human motion driven by various modalities.
AvatarGPT: All-in-One Framework for Motion Understanding, Planning, Generation and Beyond
AvatarGPT treats each task as one type of instruction fine-tuned on the shared LLM.
TLControl: Trajectory and Language Control for Human Motion Synthesis
Controllable human motion synthesis is essential for applications in AR/VR, gaming, movies, and embodied AI.
