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 26–50 of 205 papers

TitleStatusHype
NuPlan: A closed-loop ML-based planning benchmark for autonomous vehiclesCode1
Motron: Multimodal Probabilistic Human Motion ForecastingCode1
Raising context awareness in motion forecastingCode1
Expressive Forecasting of 3D Whole-body Human MotionsCode1
DenseTNT: End-to-end Trajectory Prediction from Dense Goal SetsCode1
Exploring Attention GAN for Vehicle Motion PredictionCode1
MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud SequencesCode1
Massively Multi-Person 3D Human Motion Forecasting with Scene ContextCode1
Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion ForecastingCode1
MDMP: Multi-modal Diffusion for supervised Motion Predictions with uncertaintyCode1
MotionLM: Multi-Agent Motion Forecasting as Language ModelingCode1
INT2: Interactive Trajectory Prediction at IntersectionsCode1
Contact-aware Human Motion ForecastingCode1
Efficient Baselines for Motion Prediction in Autonomous DrivingCode1
Energy-based Potential Games for Joint Motion Forecasting and ControlCode1
Are socially-aware trajectory prediction models really socially-aware?Code1
M3CAD: Towards Generic Cooperative Autonomous Driving BenchmarkCode1
Large Language Models Powered Context-aware Motion Prediction in Autonomous DrivingCode1
HOME: Heatmap Output for future Motion EstimationCode1
Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory RasterizationCode1
Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP BenchmarkCode1
Learning Cooperative Trajectory Representations for Motion ForecastingCode1
GaitForeMer: Self-Supervised Pre-Training of Transformers via Human Motion Forecasting for Few-Shot Gait Impairment Severity EstimationCode1
Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?Code1
GANet: Goal Area Network for Motion ForecastingCode1
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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