SOTAVerified

Trajectory Prediction

Trajectory Prediction is the problem of predicting the short-term (1-3 seconds) and long-term (3-5 seconds) spatial coordinates of various road-agents such as cars, buses, pedestrians, rickshaws, and animals, etc. These road-agents have different dynamic behaviors that may correspond to aggressive or conservative driving styles.

Source: Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs

Papers

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Showing 1–10 of 1004 papers

TitleStatusHype
Multi-Strategy Improved Snake Optimizer Accelerated CNN-LSTM-Attention-Adaboost for Trajectory Prediction—0
ILNet: Trajectory Prediction with Inverse Learning Attention for Enhancing Intention CaptureCode0
GoIRL: Graph-Oriented Inverse Reinforcement Learning for Multimodal Trajectory Prediction—0
AnchorDP3: 3D Affordance Guided Sparse Diffusion Policy for Robotic Manipulation—0
FlightKooba: A Fast Interpretable FTP Model—0
SceneAware: Scene-Constrained Pedestrian Trajectory Prediction with LLM-Guided WalkabilityCode0
Recent Advances in Multi-Agent Human Trajectory Prediction: A Comprehensive Review—0
IntTrajSim: Trajectory Prediction for Simulating Multi-Vehicle driving at Signalized Intersections—0
TrajFlow: Multi-modal Motion Prediction via Flow Matching—0
Egocentric Event-Based Vision for Ping Pong Ball Trajectory PredictionCode1
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All datasetsnuScenesStanford DroneETH/UCYETHJAADPIEActEVINTERACTION Dataset - ValidationPAIDTrajNetApolloScapeHEV-I

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Social LSTMFDE1.17—Unverified
2U-LSTM + Social PoolingFDE1.15—Unverified
3Social-NCE + Social-LSTMFDE1.14—Unverified