1 citations · 2 across the 10 of their papers we have counts for
12 papers
Streaming Multi-Track Timeline Control for 3D Human Motion Generation
Yangsong Zhang, Anujith Muraleedharan, Rikhat Akizhanov +3
Text-driven human motion generation has advanced substantially, yet most methods assume instructions are available before synthesis. Interactive applications require responding to…
PhysMoDPO: Physically-Plausible Humanoid Motion with Preference Optimization
Yangsong Zhang, Anujith Muraleedharan, Rikhat Akizhanov +5
Recent progress in text-conditioned human motion generation has been largely driven by diffusion models trained on large-scale human motion data. Building on this progress, recent…
Dense Motion Captioning
Shiyao Xu, Benedetta Liberatori, Gül Varol +1
Recent advances in 3D human motion and language integration have primarily focused on text-to-motion generation, leaving the task of motion understanding relatively unexplored. We…
InterPose: Learning to Generate Human-Object Interactions from Large-Scale Web Videos
Yangsong Zhang, Abdul Ahad Butt, Gül Varol +1
Human motion generation has shown great advances thanks to the recent diffusion models trained on large-scale motion capture data. Most of existing works, however, currently target…
Text-Driven 3D Hand Motion Generation from Sign Language Data
Léore Bensabath, Mathis Petrovich, Gül Varol
Our goal is to train a generative model of 3D hand motions, conditioned on natural language descriptions specifying motion characteristics such as handshapes, locations, finger/han…
MotionFix: Text-Driven 3D Human Motion Editing
Nikos Athanasiou, Alpár Cseke, Markos Diomataris +2
The focus of this paper is on 3D motion editing. Given a 3D human motion and a textual description of the desired modification, our goal is to generate an edited motion as describe…
A Cross-Dataset Study for Text-based 3D Human Motion Retrieval
Léore Bensabath, Mathis Petrovich, Gül Varol
We provide results of our study on text-based 3D human motion retrieval and particularly focus on cross-dataset generalization. Due to practical reasons such as dataset-specific hu…
Multi-Track Timeline Control for Text-Driven 3D Human Motion Generation
Mathis Petrovich, Or Litany, Umar Iqbal +4
Recent advances in generative modeling have led to promising progress on synthesizing 3D human motion from text, with methods that can generate character animations from short prom…
TMR: Text-to-Motion Retrieval Using Contrastive 3D Human Motion Synthesis
Mathis Petrovich, Michael J. Black, Gül Varol
In this paper, we present TMR, a simple yet effective approach for text to 3D human motion retrieval. While previous work has only treated retrieval as a proxy evaluation metric, w…
SINC: Spatial Composition of 3D Human Motions for Simultaneous Action Generation
Nikos Athanasiou, Mathis Petrovich, Michael J. Black +1
Our goal is to synthesize 3D human motions given textual inputs describing simultaneous actions, for example 'waving hand' while 'walking' at the same time. We refer to generating…
TEACH: Temporal Action Composition for 3D Humans
Nikos Athanasiou, Mathis Petrovich, Michael J. Black +1
Given a series of natural language descriptions, our task is to generate 3D human motions that correspond semantically to the text, and follow the temporal order of the instruction…
Action-Conditioned 3D Human Motion Synthesis with Transformer VAE
Mathis Petrovich, Michael J. Black, Gül Varol
We tackle the problem of action-conditioned generation of realistic and diverse human motion sequences. In contrast to methods that complete, or extend, motion sequences, this task…