Papers Human Pose Forecasting
“Human Pose Forecasting” 태그가 달린 논문 60편 · 필터 해제
Emotion-Conditioned Short-Horizon Human Pose Forecasting with a Lightweight Predictive World Model
Short-term human pose prediction plays a crucial role in interactive systems, assistive robots, and emotion-aware human-computer interaction[1-3]. While current trajectory prediction models primarily rely on geometric mo…
Human Pose ForecastingTrajectory PredictionPose PredictionScriboora: Rethinking Human Pose Forecasting
Human pose forecasting predicts future poses based on past observations, and has many significant applications in areas such as action recognition, autonomous driving or human-robot interaction. This paper evaluates a wi…
Human Pose ForecastingAction RecognitionAutonomous DrivingPose EstimationMotionMap: Representing Multimodality in Human Pose Forecasting
Human pose forecasting is inherently multimodal since multiple futures exist for an observed pose sequence. However, evaluating multimodality is challenging since the task is ill-posed. Therefore, we first propose an alt…
Human Pose ForecastingEgoCast: Forecasting Egocentric Human Pose in the Wild
Accurately estimating and forecasting human body pose is important for enhancing the user's sense of immersion in Augmented Reality. Addressing this need, our paper introduces EgoCast, a bimodal method for 3D human pose …
Human Pose ForecastingMotion EstimationPose EstimationMulti-agent Long-term 3D Human Pose Forecasting via Interaction-aware Trajectory Conditioning
Human pose forecasting garners attention for its diverse applications. However, challenges in modeling the multi-modal nature of human motion and intricate interactions among agents persist, particularly with longer time…
Human Pose ForecastingExploring 3D Human Pose Estimation and Forecasting from the Robot's Perspective: The HARPER Dataset
We introduce HARPER, a novel dataset for 3D body pose estimation and forecast in dyadic interactions between users and Spot, the quadruped robot manufactured by Boston Dynamics. The key-novelty is the focus on the robot'…
3D Human Pose EstimationHuman Pose ForecastingPose EstimationContext-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting
Human motion prediction is still an open problem extremely important for autonomous driving and safety applications. Due to the complex spatiotemporal relation of motion sequences, this remains a challenging problem not …
Autonomous DrivingHuman motion predictionHuman Pose ForecastingMotion Forecasting+2Expressive Forecasting of 3D Whole-body Human Motions
Human motion forecasting, with the goal of estimating future human behavior over a period of time, is a fundamental task in many real-world applications. However, existing works typically concentrate on predicting the ma…
Human Pose ForecastingMotion ForecastingGCNext: Towards the Unity of Graph Convolutions for Human Motion Prediction
The past few years has witnessed the dominance of Graph Convolutional Networks (GCNs) over human motion prediction.Various styles of graph convolutions have been proposed, with each one meticulously designed and incorpor…
Human motion predictionHuman Pose Forecastingmotion predictionUnityPersonalized Pose Forecasting
Human pose forecasting is the task of predicting articulated human motion given past human motion. There exists a number of popular benchmarks that evaluate an array of different models performing human pose forecasting.…
Human Pose ForecastingMotion ForecastingTime SeriesTime Series AnalysisDual Quaternion Rotational and Translational Equivariance in 3D Rigid Motion Modelling
Objects' rigid motions in 3D space are described by rotations and translations of a highly-correlated set of points, each with associated $x,y,z$ coordinates that real-valued networks consider as separate entities, losin…
Human Pose ForecastingScene-aware Human Motion Forecasting via Mutual Distance Prediction
In this paper, we tackle the problem of scene-aware 3D human motion forecasting. A key challenge of this task is to predict future human motions that are consistent with the scene by modeling the human-scene interactions…
Human Pose ForecastingMotion ForecastingStaged Contact-Aware Global Human Motion Forecasting
Scene-aware global human motion forecasting is critical for manifold applications, including virtual reality, robotics, and sports. The task combines human trajectory and pose forecasting within the provided scene contex…
Human Pose ForecastingMotion EstimationMotion ForecastingTrajectory Forecasting+1AnyPose: Anytime 3D Human Pose Forecasting via Neural Ordinary Differential Equations
Anytime 3D human pose forecasting is crucial to synchronous real-world human-machine interaction, where the term ``anytime" corresponds to predicting human pose at any real-valued time step. However, to the best of our k…
Human Pose ForecastingInterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion
This paper addresses a novel task of anticipating 3D human-object interactions (HOIs). Most existing research on HOI synthesis lacks comprehensive whole-body interactions with dynamic objects, e.g., often limited to mani…
3D Human DynamicsHuman DynamicsHuman motion predictionHuman-Object Interaction Detection+5Multiscale Residual Learning of Graph Convolutional Sequence Chunks for Human Motion Prediction
A new method is proposed for human motion prediction by learning temporal and spatial dependencies. Recently, multiscale graphs have been developed to model the human body at higher abstraction levels, resulting in more …
Human motion predictionHuman Pose Forecastingmotion predictionPredictionAuxiliary Tasks Benefit 3D Skeleton-based Human Motion Prediction
Exploring spatial-temporal dependencies from observed motions is one of the core challenges of human motion prediction. Previous methods mainly focus on dedicated network structures to model the spatial and temporal depe…
Human motion predictionHuman Pose Forecastingmotion predictionA Unified Masked Autoencoder with Patchified Skeletons for Motion Synthesis
The synthesis of human motion has traditionally been addressed through task-dependent models that focus on specific challenges, such as predicting future motions or filling in intermediate poses conditioned on known key-…
Human Pose ForecastingMotion SynthesisTransFusion: A Practical and Effective Transformer-based Diffusion Model for 3D Human Motion Prediction
Predicting human motion plays a crucial role in ensuring a safe and effective human-robot close collaboration in intelligent remanufacturing systems of the future. Existing works can be categorized into two groups: those…
Human motion predictionHuman Pose Forecastingmotion predictionMultimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection
Anomalies are rare and anomaly detection is often therefore framed as One-Class Classification (OCC), i.e. trained solely on normalcy. Leading OCC techniques constrain the latent representations of normal motions to limi…
2D Human Pose EstimationAnomaly DetectionHuman Pose ForecastingOne-Class Classification+1