3 papers
cs.CV2023
IA-LSTM: Interaction-Aware LSTM for Pedestrian Trajectory Prediction
Yuehai Chen
Predicting the trajectory of pedestrians in crowd scenarios is indispensable in self-driving or autonomous mobile robot field because estimating the future locations of pedestrians…
cs.CV2023
Learning Discriminative Features for Crowd Counting
Yuehai Chen, Qingzhong Wang, Jing Yang +3
Crowd counting models in highly congested areas confront two main challenges: weak localization ability and difficulty in differentiating between foreground and background, leading…
cs.CV2023
Tolerating Annotation Displacement in Dense Object Counting via Point Annotation Probability Map
Yuehai Chen, Jing Yang, Badong Chen +2
Counting objects in crowded scenes remains a challenge to computer vision. The current deep learning based approach often formulate it as a Gaussian density regression problem. Suc…