186 citations · 200 across the 12 of their papers we have counts for
12 papers
Latent Space Energy-based Model for Fine-grained Open Set Recognition
Wentao Bao, Qi Yu, Yu Kong
Fine-grained open-set recognition (FineOSR) aims to recognize images belonging to classes with subtle appearance differences while rejecting images of unknown classes. A recent tre…
On Model Explanations with Transferable Neural Pathways
Xinmiao Lin, Wentao Bao, Qi Yu +1
Neural pathways as model explanations consist of a sparse set of neurons that provide the same level of prediction performance as the whole model. Existing methods primarily focus…
Prompting Language-Informed Distribution for Compositional Zero-Shot Learning
Wentao Bao, Lichang Chen, Heng Huang +1
Compositional zero-shot learning (CZSL) task aims to recognize unseen compositional visual concepts, e.g., sliced tomatoes, where the model is learned only from the seen compositio…
GateHUB: Gated History Unit with Background Suppression for Online Action Detection
Junwen Chen, Gaurav Mittal, Ye Yu +2
Online action detection is the task of predicting the action as soon as it happens in a streaming video. A major challenge is that the model does not have access to the future and…
A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations
Krishna Prasad Neupane, Ervine Zheng, Yu Kong +1
We present a novel dynamic recommendation model that focuses on users who have interactions in the past but turn relatively inactive recently. Making effective recommendations to t…
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,…
An Eye for an Eye: Defending against Gradient-based Attacks with Gradients
Hanbin Hong, Yuan Hong, Yu Kong
Deep learning models have been shown to be vulnerable to adversarial attacks. In particular, gradient-based attacks have demonstrated high success rates recently. The gradient meas…
Gradient Frequency Modulation for Visually Explaining Video Understanding Models
Xinmiao Lin, Wentao Bao, Matthew Wright +1
In many applications, it is essential to understand why a machine learning model makes the decisions it does, but this is inhibited by the black-box nature of state-of-the-art neur…
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…