3 accepted papers
"In this work, we emphasize and demonstrate the importance of visual relation learning for motion forecasting task in autonomous driving (AD). Since exploiting the benefits of RGB images in the existing vision-based joint perception and prediction (PnP) networks is limited in the perception stage, w…
Social relations have substantial impacts on the potential trajectories of each individual. Modeling these dynamics has been a central solution for more precise and accurate trajectory forecasting. However previous works ignore the importance of `social depth' meaning the influences flowing from dif…
"Predicting future trajectories for other road agents is an essential task for autonomous vehicles. Established trajectory prediction methods primarily use agent tracks generated by a detection and tracking system and HD map as inputs. In this work, we propose a novel method that also incorporates v…