Papers motion in-betweening
“motion in-betweening” 태그가 달린 논문 17편 · 필터 해제
SILK: Smooth InterpoLation frameworK for motion in-betweening A Simplified Computational Approach
Motion in-betweening is a crucial tool for animators, enabling intricate control over pose-level details in each keyframe. Recent machine learning solutions for motion in-betweening rely on complex models, incorporating …
motion in-betweeningMotion InterpolationSceneMI: Motion In-betweening for Modeling Human-Scene Interactions
Modeling human-scene interactions (HSI) is essential for understanding and simulating everyday human behaviors. Recent approaches utilizing generative modeling have made progress in this domain; however, they are limited…
Denoisingmotion in-betweeningVersatile Physics-based Character Control with Hybrid Latent Representation
We present a versatile latent representation that enables physically simulated character to efficiently utilize motion priors. To build a powerful motion embedding that is shared across multiple tasks, the physics contro…
Motion Generationmotion in-betweeningQuantizationDiffuse-CLoC: Guided Diffusion for Physics-based Character Look-ahead Control
We present Diffuse-CLoC, a guided diffusion framework for physics-based look-ahead control that enables intuitive, steerable, and physically realistic motion generation. While existing kinematics motion generation with d…
Action GenerationMotion Generationmotion in-betweeningAnyMoLe: Any Character Motion In-betweening Leveraging Video Diffusion Models
Despite recent advancements in learning-based motion in-betweening, a key limitation has been overlooked: the requirement for character-specific datasets. In this work, we introduce AnyMoLe, a novel method that addresses…
Motion Generationmotion in-betweeningMotion SynthesisTowards Synthesized and Editable Motion In-Betweening Through Part-Wise Phase Representation
Styled motion in-betweening is crucial for computer animation and gaming. However, existing methods typically encode motion styles by modeling whole-body motions, often overlooking the representation of individual body p…
motion in-betweeningReal-time Diverse Motion In-betweening with Space-time Control
In this work, we present a data-driven framework for generating diverse in-betweening motions for kinematic characters. Our approach injects dynamic conditions and explicit motion controls into the procedure of motion tr…
motion in-betweeningMoManifold: Learning to Measure 3D Human Motion via Decoupled Joint Acceleration Manifolds
Incorporating temporal information effectively is important for accurate 3D human motion estimation and generation which have wide applications from human-computer interaction to AR/VR. In this paper, we present MoManifo…
DenoisingHuman DynamicsMotion Estimationmotion in-betweeningFlexible Motion In-betweening with Diffusion Models
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…
Imputationmotion in-betweeningHandDiffuse: Generative Controllers for Two-Hand Interactions via Diffusion Models
Existing hands datasets are largely short-range and the interaction is weak due to the self-occlusion and self-similarity of hands, which can not yet fit the need for interacting hands motion generation. To rescue the da…
Data AugmentationMotion Generationmotion in-betweeningTemporal SequencesMMM: Generative Masked Motion Model
Recent advances in text-to-motion generation using diffusion and autoregressive models have shown promising results. However, these models often suffer from a trade-off between real-time performance, high fidelity, and m…
GPUmodelMotion Generationmotion in-betweening+1Motion In-Betweening with Phase Manifolds
This paper introduces a novel data-driven motion in-betweening system to reach target poses of characters by making use of phases variables learned by a Periodic Autoencoder. Our approach utilizes a mixture-of-experts ne…
Mixture-of-Expertsmotion in-betweeningDiverse Motion In-betweening with Dual Posture Stitching
In-betweening is a technique for generating transitions given initial and target character states. The majority of existing works require multiple (often $>$10) frames as input, which are not always accessible. Our work …
motion in-betweeningSkeleton2Humanoid: Animating Simulated Characters for Physically-plausible Motion In-betweening
Human motion synthesis is a long-standing problem with various applications in digital twins and the Metaverse. However, modern deep learning based motion synthesis approaches barely consider the physical plausibility of…
motion in-betweeningMotion SynthesisReinforcement Learning (RL)Test-time AdaptationFLAME: Free-form Language-based Motion Synthesis & Editing
Text-based motion generation models are drawing a surge of interest for their potential for automating the motion-making process in the game, animation, or robot industries. In this paper, we propose a diffusion-based mo…
FormMotion Generationmotion in-betweeningmotion prediction+1Conditional Motion In-betweening
Motion in-betweening (MIB) is a process of generating intermediate skeletal movement between the given start and target poses while preserving the naturalness of the motion, such as periodic footstep motion while walking…
Motion Generationmotion in-betweeningPose PredictionRobust Motion In-betweening
In this work we present a novel, robust transition generation technique that can serve as a new tool for 3D animators, based on adversarial recurrent neural networks. The system synthesizes high-quality motions that use …
Human Pose Forecastingmotion in-betweeningmotion predictionMotion Synthesis