SOTAVerified

Motion Forecasting

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

Papers

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Showing 181–190 of 205 papers

TitleStatusHype
Learning Lane Graph Representations for Motion ForecastingCode1
SMART: Simultaneous Multi-Agent Recurrent Trajectory Prediction—0
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting—0
Probabilistic Multi-modal Trajectory Prediction with Lane Attention for Autonomous Vehicles—0
One Thousand and One Hours: Self-driving Motion Prediction DatasetCode0
The Importance of Prior Knowledge in Precise Multimodal Prediction—0
PnPNet: End-to-End Perception and Prediction with Tracking in the Loop—0
RV-FuseNet: Range View Based Fusion of Time-Series LiDAR Data for Joint 3D Object Detection and Motion Forecasting—0
Towards Streaming PerceptionCode1
A Deep Learning Approach for Motion Forecasting Using 4D OCT Data—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