Publications de Yang Gao | EPFL Graph Search

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Accurate human trajectory prediction is one of the most crucial tasks for autonomous driving, ensuring its safety. Yet, existing models often fail to fully leverage the visual cues that humans subconsciously communicate when navigating the space. In this w ...

Conventional human trajectory prediction models rely on clean curated data, requiring specialized equipment or manual labeling, which is often impractical for robotic applications. The existing predictors tend to overfit to clean observation affecting thei ...

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

Predicting future trajectories is critical in autonomous driving, especially in preventing accidents involving humans, where a predictive agent’s ability to anticipate in advance is of utmost importance. Trajectory forecasting models, employed in fields su ...

Yang Gao

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Social-Pose: Enhancing Trajectory Prediction with Human Body Pose

Unified Human Localization and Trajectory Prediction with Monocular Vision

Social-Transmotion: Promptable Human Trajectory Prediction

JRDB-Traj: A Dataset and Benchmark for Trajectory Forecasting in Crowds