motion prediction
188 papers with code • 0 benchmarks • 13 datasets
Benchmarks
These leaderboards are used to track progress in motion prediction
Libraries
Use these libraries to find motion prediction models and implementationsDatasets
UCY
Waymo Open Motion Dataset
Argoverse 2 Motion Forecasting
Expi
SinD
GTA-IM Dataset
NTU RGB+D 2D
Lyft Level 5 Prediction
Latest papers
StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation
hvision-nku/storydiffusion
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This module converts the generated sequence of images into videos with smooth transitions and consistent subjects that are significantly more stable than the modules based on latent spaces only, especially in the context of long video generation.
ADM: Accelerated Diffusion Model via Estimated Priors for Robust Motion Prediction under Uncertainties
However, the significant time consumption and sensitivity to noise have limited the real-time predictive capability of diffusion models.
Motor Focus: Ego-Motion Prediction with All-Pixel Matching
Furthermore, in the experiments part, we show the qualitative analysis of motor focus estimation between the conventional dense optical flow-based method and the proposed method.
OFMPNet: Deep End-to-End Model for Occupancy and Flow Prediction in Urban Environment
The task of motion prediction is pivotal for autonomous driving systems, providing crucial data to choose a vehicle behavior strategy within its surroundings.
PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving
sair-lab/physord
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To bridge this gap, we present PhysORD, a neural-symbolic approach integrating the conservation law, i. e., the Euler-Lagrange equation, into data-driven neural models for motion prediction in off-road driving.
Self-Supervised Class-Agnostic Motion Prediction with Spatial and Temporal Consistency Regularizations
kwwcv/selfmotion
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To this end, we explore the feasibility of self-supervised motion prediction with only unlabeled LiDAR point clouds.
SmartRefine: A Scenario-Adaptive Refinement Framework for Efficient Motion Prediction
Context information, such as road maps and surrounding agents' states, provides crucial geometric and semantic information for motion behavior prediction.
Context-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.
GenAD: Generative End-to-End Autonomous Driving
wzzheng/genad
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We then employ a variational autoencoder to learn the future trajectory distribution in a structural latent space for trajectory prior modeling.
SIMPL: A Simple and Efficient Multi-agent Motion Prediction Baseline for Autonomous Driving
hkust-aerial-robotics/simpl
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This paper presents a Simple and effIcient Motion Prediction baseLine (SIMPL) for autonomous vehicles.
