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Papers › OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising

OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising

2 Apr 2024CVPR 2024 1arXiv:2404.02227archive 2025-07-28

Haichao Zhang, Yi Xu, HongSheng Lu, Takayuki Shimizu, Yun Fu

Trajectory prediction is fundamental in computer vision and autonomous driving, particularly for understanding pedestrian behavior and enabling proactive decision-making. Existing approaches in this field often assume precise and complete observational data, neglecting the challenges associated with out-of-view objects and the noise inherent in sensor data due to limited camera range, physical obstructions, and the absence of ground truth for denoised sensor data. Such oversights are critical safety concerns, as they can result in missing essential, non-visible objects. To bridge this gap, we present a novel method for out-of-sight trajectory prediction that leverages a vision-positioning technique. Our approach denoises noisy sensor observations in an unsupervised manner and precisely maps sensor-based trajectories of out-of-sight objects into visual trajectories. This method has demonstrated state-of-the-art performance in out-of-sight noisy sensor trajectory denoising and prediction on the Vi-Fi and JRDB datasets. By enhancing trajectory prediction accuracy and addressing the challenges of out-of-sight objects, our work significantly contributes to improving the safety and reliability of autonomous driving in complex environments. Our work represents the first initiative towards Out-Of-Sight Trajectory prediction (OOSTraj), setting a new benchmark for future research. The code is available at \url{https://github.com/Hai-chao-Zhang/OOSTraj}.

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hai-chao-zhang/oostraj officialmentioned in papermentioned on GitHubpytorch report

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Tasks

Autonomous DrivingDecision MakingDenoisingOut-of-Sight Trajectory PredictionPredictionTrajectory Prediction

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset OOSTraj MSE-D 13.42 #1 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset OOSTraj MSE-P 13.83 #1 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset OOSTraj SUM 27.24 #1 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset Transformer MSE-D 14.26 #2 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset Transformer MSE-P 14.08 #2 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset Transformer SUM 28.33 #2 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset RNN MSE-D 15.92 #3 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset RNN MSE-P 15.69 #3 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset RNN SUM 31.61 #3 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset GRU MSE-D 28.69 #4 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset GRU MSE-P 28.65 #4 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset GRU SUM 57.34 #4 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset LSTM MSE-D 58.31 #5 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset LSTM MSE-P 57.7 #5 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset LSTM SUM 116.01 #5 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset ViTag MSE-D 100.53 #6 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset ViTag MSE-P 100.37 #6 of 6 Archive leaderboard report
Out-of-Sight Trajectory Prediction Vi-Fi Multi-modal Dataset ViTag SUM 200.9 #6 of 6 Archive leaderboard report

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Methods

Introduced by this paper: OOSTraj

OOSTraj

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