Bimanual 3D Hand Motion and Articulation Forecasting in Everyday Images

2025/10/07 by Aditya Prakash, David Forsyth, Prakash, Aditya +3
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Hand Gesture Recognition Systems #Human Motion and Animation #Human Pose and Action Recognition #Machine Learning (cs.LG)

paper · pdf · doi:10.48550/arxiv.2510.06145

openalex publication_date 2025/10/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We tackle the problem of forecasting bimanual 3D hand motion & articulation from a single image in everyday settings. To address the lack of 3D hand annotations in diverse settings, we design an annotation pipeline consisting of a diffusion model to lift 2D hand keypoint sequences to 4D hand motion. For the forecasting model, we adopt a diffusion loss to account for the multimodality in hand motion distribution. Extensive experiments across 6 datasets show the benefits of training on diverse data with imputed labels (14% improvement) and effectiveness of our lifting (42% better) & forecasting (16.4% gain) models, over the best baselines, especially in zero-shot generalization to everyday images.

Citations

• How Do I Do That? Synthesizing 3D Hand Motion and Contacts for Everyday Interactions
• Predicting 4D Hand Trajectory from Monocular Videos
• HaWoR: World-Space Hand Motion Reconstruction from Egocentric Videos
• Dyn-HaMR: Recovering 4D Interacting Hand Motion from a Dynamic Camera
• BimArt: A Unified Approach for the Synthesis of 3D Bimanual Interaction with Articulated Objects
• Lifting Motion to the 3D World via 2D Diffusion
• Estimating Body and Hand Motion in an Ego-sensed World
• WiLoR: End-to-end 3D Hand Localization and Reconstruction in-the-wild
• ManiDext: Hand-Object Manipulation Synthesis via Continuous Correspondence Embeddings and Residual-Guided Diffusion
• An Expectation-Maximization Algorithm for Training Clean Diffusion Models from Corrupted Observations
• Introducing HOT3D: An Egocentric Dataset for 3D Hand and Object Tracking
• EM Distillation for One-step Diffusion Models
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• Benchmarks and Challenges in Pose Estimation for Egocentric Hand Interactions with Objects
• Cameras as Rays: Pose Estimation via Ray Diffusion
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• 3D Hand Pose Estimation in Everyday Egocentric Images
• Mitigating Perspective Distortion-induced Shape Ambiguity in Image Crops
• Reconstructing Hands in 3D with Transformers
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• MAS: Multi-view Ancestral Sampling for 3D motion generation using 2D diffusion
• HoloAssist: an Egocentric Human Interaction Dataset for Interactive AI Assistants in the Real World
• Uncertainty-aware State Space Transformer for Egocentric 3D Hand Trajectory Forecasting
• Ambient Diffusion: Learning Clean Distributions from Corrupted Data
• Decoupling Human and Camera Motion from Videos in the Wild
• Ego-Body Pose Estimation via Ego-Head Pose Estimation
• Human Motion Diffusion Model
• ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulation
• Joint Hand Motion and Interaction Hotspots Prediction from Egocentric Videos
• P-STMO: Pre-Trained Spatial Temporal Many-to-One Model for 3D Human Pose Estimation
• MixSTE: Seq2seq Mixed Spatio-Temporal Encoder for 3D Human Pose Estimation in Video
• ElePose: Unsupervised 3D Human Pose Estimation by Predicting Camera Elevation and Learning Normalizing Flows on 2D Poses
• GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Cameras
• MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation
• 3D Pose Estimation and Future Motion Prediction from 2D Images
• Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimation
• H2O: Two Hands Manipulating Objects for First Person Interaction\n Recognition
• DexYCB: A Benchmark for Capturing Hand Grasping of Objects
• 3D Human Pose Estimation with Spatial and Temporal Transformers
• End-to-End Human Pose and Mesh Reconstruction with Transformers
• Reconstructing Hand-Object Interactions in the Wild
• Accurate 3D Hand Pose Estimation for Whole-Body 3D Human Mesh Estimation
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose\n Estimation from a Single RGB Image
• FrankMocap: Fast Monocular 3D Hand and Body Motion Capture by Regression and Integration
• Motion Guided 3D Pose Estimation from Videos
• On the Continuity of Rotation Representations in Neural Networks
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• Hand Pose Estimation via Latent 2.5D Heatmap Regression
• A simple yet effective baseline for 3d human pose estimation
• Learning to Estimate 3D Hand Pose from Single RGB Images
• Multi-view Supervision for Single-view Reconstruction via Differentiable\n Ray Consistency
• Perspective Transformer Nets: Learning Single-View 3D Object\n Reconstruction without 3D Supervision
• 3D Human Pose Estimation from a Single Image via Distance Matrix\n Regression
• SIGHT: Synthesizing Image-Text Conditioned and Geometry-Guided 3D Hand-Object Trajectories

Related

• SFHand: A Streaming Framework for Language-guided 3D Hand Forecasting and Embodied Manipulation
• The Invisible EgoHand: 3D Hand Forecasting through EgoBody Pose Estimation
• Uni-Hand: Universal Hand Motion Forecasting in Egocentric Views
• Novel Diffusion Models for Multimodal 3D Hand Trajectory Prediction
• EMAG: Ego-motion Aware and Generalizable 2D Hand Forecasting from Egocentric Videos