Papers motion prediction
“motion prediction” 태그가 달린 논문 597편 · 필터 해제
Stochastic Human Motion Prediction with Memory of Action Transition and Action Characteristic
Action-driven stochastic human motion prediction aims to generate future motion sequences of a pre-defined target action based on given past observed sequences performing non-target actions. This task primarily presents …
Human motion predictionmotion predictionStochastic Human Motion PredictionTemporal Continual Learning with Prior Compensation for Human Motion Prediction
Human Motion Prediction (HMP) aims to predict future poses at different moments according to past motion sequences. Previous approaches have treated the prediction of various moments equally, resulting in two main limita…
Continual LearningHuman motion predictionmotion predictionAMPLIFY: Actionless Motion Priors for Robot Learning from Videos
Action-labeled data for robotics is scarce and expensive, limiting the generalization of learned policies. In contrast, vast amounts of action-free video data are readily available, but translating these observations int…
motion predictionVideo PredictionFocalAD: Local Motion Planning for End-to-End Autonomous Driving
In end-to-end autonomous driving,the motion prediction plays a pivotal role in ego-vehicle planning. However, existing methods often rely on globally aggregated motion features, ignoring the fact that planning decisions …
Autonomous DrivingBench2DriveMotion Planningmotion predictionTrajFlow: Multi-modal Motion Prediction via Flow Matching
Efficient and accurate motion prediction is crucial for ensuring safety and informed decision-making in autonomous driving, particularly under dynamic real-world conditions that necessitate multi-modal forecasts. We intr…
Autonomous Drivingmotion predictionPredictionTrajectory PredictionHUMOF: Human Motion Forecasting in Interactive Social Scenes
Complex scenes present significant challenges for predicting human behaviour due to the abundance of interaction information, such as human-human and humanenvironment interactions. These factors complicate the analysis a…
Motion Forecastingmotion predictionRodrigues Network for Learning Robot Actions
Understanding and predicting articulated actions is important in robot learning. However, common architectures such as MLPs and Transformers lack inductive biases that reflect the underlying kinematic structure of articu…
Imitation LearningInductive Biasmotion predictionAutoregression-free video prediction using diffusion model for mitigating error propagation
Existing long-term video prediction methods often rely on an autoregressive video prediction mechanism. However, this approach suffers from error propagation, particularly in distant future frames. To address this limita…
motion predictionPredictionVideo PredictionCodeMerge: Codebook-Guided Model Merging for Robust Test-Time Adaptation in Autonomous Driving
Maintaining robust 3D perception under dynamic and unpredictable test-time conditions remains a critical challenge for autonomous driving systems. Existing test-time adaptation (TTA) methods often fail in high-variance t…
3D Object DetectionAutonomous DrivingLinear Mode Connectivitymotion prediction+3APEX: Empowering LLMs with Physics-Based Task Planning for Real-time Insight
Large Language Models (LLMs) demonstrate strong reasoning and task planning capabilities but remain fundamentally limited in physical interaction modeling. Existing approaches integrate perception via Vision-Language Mod…
Causal InferenceDecision Makingmotion predictionReinforcement Learning (RL)+1UPTor: Unified 3D Human Pose Dynamics and Trajectory Prediction for Human-Robot Interaction
We introduce a unified approach to forecast the dynamics of human keypoints along with the motion trajectory based on a short sequence of input poses. While many studies address either full-body pose prediction or motion…
3D Human Pose EstimationGraph Attentionmotion predictionPose Estimation+4AGI-Elo: How Far Are We From Mastering A Task?
As the field progresses toward Artificial General Intelligence (AGI), there is a pressing need for more comprehensive and insightful evaluation frameworks that go beyond aggregate performance metrics. This paper introduc…
Code GenerationImage ClassificationMotion Planningmotion prediction+2CacheFlow: Fast Human Motion Prediction by Cached Normalizing Flow
Many density estimation techniques for 3D human motion prediction require a significant amount of inference time, often exceeding the duration of the predicted time horizon. To address the need for faster density estimat…
Density EstimationHuman motion predictionmotion predictionPredictionMulti-Resolution Haar Network: Enhancing human motion prediction via Haar transform
The 3D human pose is vital for modern computer vision and computer graphics, and its prediction has drawn attention in recent years. 3D human pose prediction aims at forecasting a human's future motion from the previous …
Human motion predictionmotion predictionPose PredictionRobust Planning for Autonomous Driving via Mixed Adversarial Diffusion Predictions
We describe a robust planning method for autonomous driving that mixes normal and adversarial agent predictions output by a diffusion model trained for motion prediction. We first train a diffusion model to learn an unbi…
Autonomous Drivingmotion predictionPatient-Specific Autoregressive Models for Organ Motion Prediction in Radiotherapy
Radiotherapy often involves a prolonged treatment period. During this time, patients may experience organ motion due to breathing and other physiological factors. Predicting and modeling this motion before treatment is c…
motion predictionHuman Motion Prediction via Test-domain-aware Adaptation with Easily-available Human Motions Estimated from Videos
In 3D Human Motion Prediction (HMP), conventional methods train HMP models with expensive motion capture data. However, the data collection cost of such motion capture data limits the data diversity, which leads to poor …
DiversityHuman motion predictionmotion predictionClosing the Loop: Motion Prediction Models beyond Open-Loop Benchmarks
Fueled by motion prediction competitions and benchmarks, recent years have seen the emergence of increasingly large learning based prediction models, many with millions of parameters, focused on improving open-loop predi…
Autonomous Drivingmotion predictionPredictionDynamic Network Flow Optimization for Task Scheduling in PTZ Camera Surveillance Systems
This paper presents a novel approach for optimizing the scheduling and control of Pan-Tilt-Zoom (PTZ) cameras in dynamic surveillance environments. The proposed method integrates Kalman filters for motion prediction with…
motion predictionSchedulingFuture-Oriented Navigation: Dynamic Obstacle Avoidance with One-Shot Energy-Based Multimodal Motion Prediction
This paper proposes an integrated approach for the safe and efficient control of mobile robots in dynamic and uncertain environments. The approach consists of two key steps: one-shot multimodal motion prediction to antic…
Model Predictive ControlMotion Planningmotion predictionNavigate+1