Guy Tevet
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View article: Generating Detailed Character Motion from Blocking Poses
Generating Detailed Character Motion from Blocking Poses Open
We focus on the problem of using generative diffusion models for the task of motion detailing: converting a rough version of a character animation, represented by a sparse set of coarsely posed, and imprecisely timed blocking poses, into a…
View article: Express4D: Expressive, Friendly, and Extensible 4D Facial Motion Generation Benchmark
Express4D: Expressive, Friendly, and Extensible 4D Facial Motion Generation Benchmark Open
Dynamic facial expression generation from natural language is a crucial task in Computer Graphics, with applications in Animation, Virtual Avatars, and Human-Computer Interaction. However, current generative models suffer from datasets tha…
View article: BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion
BeyondMimic: From Motion Tracking to Versatile Humanoid Control via Guided Diffusion Open
The human-like form of humanoid robots positions them uniquely to achieve the agility and versatility in motor skills that humans possess. Learning from human demonstrations offers a scalable approach to acquiring these capabilities. Howev…
View article: HOIDiNi: Human-Object Interaction through Diffusion Noise Optimization
HOIDiNi: Human-Object Interaction through Diffusion Noise Optimization Open
We present HOIDiNi, a text-driven diffusion framework for synthesizing realistic and plausible human-object interaction (HOI). HOI generation is extremely challenging since it induces strict contact accuracies alongside a diverse motion ma…
View article: AnyTop: Character Animation Diffusion with Any Topology
AnyTop: Character Animation Diffusion with Any Topology Open
Generating motion for arbitrary skeletons is a longstanding challenge in computer graphics, remaining largely unexplored due to the scarcity of diverse datasets and the irregular nature of the data. In this work, we introduce AnyTop, a dif…
View article: CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control
CLoSD: Closing the Loop between Simulation and Diffusion for multi-task character control Open
Motion diffusion models and Reinforcement Learning (RL) based control for physics-based simulations have complementary strengths for human motion generation. The former is capable of generating a wide variety of motions, adhering to intuit…
View article: Monkey See, Monkey Do: Harnessing Self-attention in Motion Diffusion for Zero-shot Motion Transfer
Monkey See, Monkey Do: Harnessing Self-attention in Motion Diffusion for Zero-shot Motion Transfer Open
Given the remarkable results of motion synthesis with diffusion models, a natural question arises: how can we effectively leverage these models for motion editing? Existing diffusion-based motion editing methods overlook the profound poten…
View article: Flexible Motion In-betweening with Diffusion Models
Flexible Motion In-betweening with Diffusion Models Open
Motion in-betweening, a fundamental task in character animation, consists of generating motion sequences that plausibly interpolate user-provided keyframe constraints. It has long been recognized as a labor-intensive and challenging proces…
View article: MAS: Multi-view Ancestral Sampling for 3D motion generation using 2D diffusion
MAS: Multi-view Ancestral Sampling for 3D motion generation using 2D diffusion Open
We introduce Multi-view Ancestral Sampling (MAS), a method for 3D motion generation, using 2D diffusion models that were trained on motions obtained from in-the-wild videos. As such, MAS opens opportunities to exciting and diverse fields o…
View article: Human Motion Diffusion as a Generative Prior
Human Motion Diffusion as a Generative Prior Open
Recent work has demonstrated the significant potential of denoising diffusion models for generating human motion, including text-to-motion capabilities. However, these methods are restricted by the paucity of annotated motion data, a focus…
View article: Single Motion Diffusion
Single Motion Diffusion Open
Synthesizing realistic animations of humans, animals, and even imaginary creatures, has long been a goal for artists and computer graphics professionals. Compared to the imaging domain, which is rich with large available datasets, the numb…
View article: Human Motion Diffusion Model
Human Motion Diffusion Model Open
Natural and expressive human motion generation is the holy grail of computer animation. It is a challenging task, due to the diversity of possible motion, human perceptual sensitivity to it, and the difficulty of accurately describing it. …
View article: Evaluating the Evaluation of Diversity in Natural Language Generation
Evaluating the Evaluation of Diversity in Natural Language Generation Open
Despite growing interest in natural language generation (NLG) models that produce diverse outputs, there is currently no principled method for evaluating the diversity of an NLG system. In this work, we propose a framework for evaluating d…
View article: Evaluating Text
Evaluating Text Open
Guy Tevet, Gavriel Habib, Vered Shwartz, Jonathan Berant. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 201…
View article: Evaluating Text GANs as Language Models
Evaluating Text GANs as Language Models Open
Generative Adversarial Networks (GANs) are a promising approach for text generation that, unlike traditional language models (LM), does not suffer from the problem of ``exposure bias''. However, A major hurdle for understanding the potenti…