no code implementations • ECCV 2020 • Huikun Bi, Ruisi Zhang, Tianlu Mao, Zhigang Deng, Zhaoqi Wang
This work presents a novel First-person View based Trajectory predicting model (FvTraj) to estimate the future trajectories of pedestrians in a scene given their observed trajectories and the corresponding first-person view images.
no code implementations • 17 Aug 2023 • Zijian Song, Huikun Bi, Ruisi Zhang, Tianlu Mao, Zhaoqi Wang
We presented a cross-view trajectory prediction method using shared 3D Queries (XVTP3D).
no code implementations • ICCV 2019 • Huikun Bi, Zhong Fang, Tianlu Mao, Zhaoqi Wang, Zhigang Deng
In order to evaluate our model, a large dataset containing the trajectories of both vehicles and pedestrians in vehicle-pedestrian-mixed scenes is specially built.