Trajectory Prediction
252 papers with code • 29 benchmarks • 34 datasets
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
Benchmarks
These leaderboards are used to track progress in Trajectory Prediction
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Libraries
Use these libraries to find Trajectory Prediction models and implementationsDatasets
nuScenes
Argoverse
UCY
highD Dataset
INTERACTION Dataset
Waymo Open Motion Dataset
ApolloScape
ETH
inD Dataset
HDD
Most implemented papers
Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction
abduallahmohamed/Social-STGCNN
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CVPR 2020
Better machine understanding of pedestrian behaviors enables faster progress in modeling interactions between agents such as autonomous vehicles and humans.
Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation
Inspired by human navigation, we model the task of trajectory prediction as an intuitive two-stage process: (i) goal estimation, which predicts the most likely target positions of the agent, followed by a (ii) routing module which estimates a set of plausible trajectories that route towards the estimated goal.
OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets
Human Trajectory Prediction (HTP) has gained much momentum in the last years and many solutions have been proposed to solve it.
Exploring Dynamic Context for Multi-path Trajectory Prediction
wtliao/DCENet
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In our framework, first, the spatial context between agents is explored by using self-attention architectures.
Trajformer: Trajectory Prediction with Local Self-Attentive Contexts for Autonomous Driving
Effective feature-extraction is critical to models' contextual understanding, particularly for applications to robotics and autonomous driving, such as multimodal trajectory prediction.
From Goals, Waypoints & Paths To Long Term Human Trajectory Forecasting
harshayugirase/human-path-prediction
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ICCV 2021
Uncertainty in future trajectories stems from two sources: (a) sources that are known to the agent but unknown to the model, such as long term goals and (b)sources that are unknown to both the agent & the model, such as intent of other agents & irreducible randomness indecisions.
Principled Simplicial Neural Networks for Trajectory Prediction
We consider the construction of neural network architectures for data on simplicial complexes.
Latent Variable Sequential Set Transformers For Joint Multi-Agent Motion Prediction
roggirg/AutoBots
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ICLR 2022
AutoBots can produce either the trajectory of one ego-agent or a distribution over the future trajectories for all agents in the scene.
AgentFormer: Agent-Aware Transformers for Socio-Temporal Multi-Agent Forecasting
Khrylx/AgentFormer
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ICCV 2021
Instead, we would prefer a method that allows an agent's state at one time to directly affect another agent's state at a future time.
DenseTNT: End-to-end Trajectory Prediction from Dense Goal Sets
Tsinghua-MARS-Lab/DenseTNT
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ICCV 2021
In this work, we propose an anchor-free and end-to-end trajectory prediction model, named DenseTNT, that directly outputs a set of trajectories from dense goal candidates.
