186 citations · 205 across the 6 of their papers we have counts for
6 papers
OpenTAL: Towards Open Set Temporal Action Localization
Wentao Bao, Qi Yu, Yu Kong
Temporal Action Localization (TAL) has experienced remarkable success under the supervised learning paradigm. However, existing TAL methods are rooted in the closed set assumption,…
Evidential Deep Learning for Open Set Action Recognition
Wentao Bao, Qi Yu, Yu Kong
In a real-world scenario, human actions are typically out of the distribution from training data, which requires a model to both recognize the known actions and reject the unknown.…
DRIVE: Deep Reinforced Accident Anticipation with Visual Explanation
Wentao Bao, Qi Yu, Yu Kong
Traffic accident anticipation aims to accurately and promptly predict the occurrence of a future accident from dashcam videos, which is vital for a safety-guaranteed self-driving s…
Group Activity Prediction with Sequential Relational Anticipation Model
Junwen Chen, Wentao Bao, Yu Kong
In this paper, we propose a novel approach to predict group activities given the beginning frames with incomplete activity executions. Existing action prediction approaches learn t…
Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning
Wentao Bao, Qi Yu, Yu Kong
Traffic accident anticipation aims to predict accidents from dashcam videos as early as possible, which is critical to safety-guaranteed self-driving systems. With cluttered traffi…
Object-Aware Centroid Voting for Monocular 3D Object Detection
Wentao Bao, Qi Yu, Yu Kong
Monocular 3D object detection aims to detect objects in a 3D physical world from a single camera. However, recent approaches either rely on expensive LiDAR devices, or resort to de…