186 citations · 216 across the 17 of their papers we have counts for
18 papers
Open Set Face Forgery Detection via Dual-Level Evidence Collection
Zhongyi Cai, Bryce Gernon, Wentao Bao +3
The surge in face forgeries has increasingly undermined confidence in the authenticity of online content. As generation algorithms rapidly evolve, new fake categories will constant…
Window Token Concatenation for Efficient Visual Large Language Models
Yifan Li, Wentao Bao, Botao Ye +4
To effectively reduce the visual tokens in Visual Large Language Models (VLLMs), we propose a novel approach called Window Token Concatenation (WiCo). Specifically, we employ a sli…
Visual Large Language Models for Generalized and Specialized Applications
Yifan Li, Zhixin Lai, Wentao Bao +7
Visual-language models (VLM) have emerged as a powerful tool for learning a unified embedding space for vision and language. Inspired by large language models, which have demonstra…
Exploiting VLM Localizability and Semantics for Open Vocabulary Action Detection
Wentao Bao, Kai Li, Yuxiao Chen +3
Action detection aims to detect (recognize and localize) human actions spatially and temporally in videos. Existing approaches focus on the closed-set setting where an action detec…
Learning to Localize Actions in Instructional Videos with LLM-Based Multi-Pathway Text-Video Alignment
Yuxiao Chen, Kai Li, Wentao Bao +4
Learning to localize temporal boundaries of procedure steps in instructional videos is challenging due to the limited availability of annotated large-scale training videos. Recent…
Facial Affective Behavior Analysis with Instruction Tuning
Yifan Li, Anh Dao, Wentao Bao +4
Facial affective behavior analysis (FABA) is crucial for understanding human mental states from images. However, traditional approaches primarily deploy models to discriminate amon…
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…
Uncertainty-aware State Space Transformer for Egocentric 3D Hand Trajectory Forecasting
Wentao Bao, Lele Chen, Libing Zeng +4
Hand trajectory forecasting from egocentric views is crucial for enabling a prompt understanding of human intentions when interacting with AR/VR systems. However, existing methods…
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…
Towards Open Set Video Anomaly Detection
Yuansheng Zhu, Wentao Bao, Qi Yu
Open Set Video Anomaly Detection (OpenVAD) aims to identify abnormal events from video data where both known anomalies and novel ones exist in testing. Unsupervised models learned…
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,…
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…
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…