SOTAVerified

Motion Forecasting

Motion forecasting is the task of predicting the location of a tracked object in the future

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–125 of 205 papers

TitleStatusHype
SSL-Interactions: Pretext Tasks for Interactive Trajectory Prediction—0
StopNet: Scalable Trajectory and Occupancy Prediction for Urban Autonomous Driving—0
TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understanding—0
Target-driven Self-Distillation for Partial Observed Trajectories Forecasting—0
BANet: Motion Forecasting with Boundary Aware Network—0
TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Prediction—0
Test-time Personalizable Forecasting of 3D Human Poses—0
The 2nd Place Solution for 2023 Waymo Open Sim Agents Challenge—0
The Importance of Prior Knowledge in Precise Multimodal Prediction—0
The WayHome: Long-term Motion Prediction on Dynamically Scaled—0
TPCN: Temporal Point Cloud Networks for Motion Forecasting—0
TrajSSL: Trajectory-Enhanced Semi-Supervised 3D Object Detection—0
TSGN: Temporal Scene Graph Neural Networks with Projected Vectorized Representation for Multi-Agent Motion Prediction—0
VALISENS: A Validated Innovative Multi-Sensor System for Cooperative Automated Driving—0
Vectorized Representation Dreamer (VRD): Dreaming-Assisted Multi-Agent Motion-Forecasting—0
Vehicle Motion Forecasting using Prior Information and Semantic-assisted Occupancy Grid Maps—0
VN-Transformer: Rotation-Equivariant Attention for Vector Neurons—0
Where computer vision can aid physics: dynamic cloud motion forecasting from satellite images—0
WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting—0
Forecasting Future Videos from Novel Views via Disentangled 3D Scene Representation—0
Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers—0
Scaling Laws of Motion Forecasting and Planning -- A Technical Report—0
Adaptive Prediction Ensemble: Improving Out-of-Distribution Generalization of Motion Forecasting—0
A Deep Learning Approach for Motion Forecasting Using 4D OCT Data—0
AMP: Autoregressive Motion Prediction Revisited with Next Token Prediction for Autonomous Driving—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1WSTbrier-minFDE (K=6)26.41—Unverified
2BaseballBrobrier-minFDE (K=6)24.35—Unverified
3Constant velocity map priorbrier-minFDE (K=6)23.39—Unverified
4DQSbrier-minFDE (K=6)12.88—Unverified
5xjtub09brier-minFDE (K=6)11.46—Unverified
6suubrier-minFDE (K=6)9.51—Unverified
7yellowtaxibrier-minFDE (K=6)8.86—Unverified
8Online_CLbrier-minFDE (K=6)8.75—Unverified
9RuShengbrier-minFDE (K=6)8.38—Unverified
10mmmdddbrier-minFDE (K=6)8.26—Unverified