Search Results for author: Wentao Bao

Found 13 papers, 6 papers with code

Latent Space Energy-based Model for Fine-grained Open Set Recognition

no code implementations19 Sep 2023 Wentao Bao, Qi Yu, Yu Kong

A recent trend in OSR shows the benefit of generative models to discriminative unknown detection.

Attribute Density Estimation +1

On Model Explanations with Transferable Neural Pathways

no code implementations18 Sep 2023 Xinmiao Lin, Wentao Bao, Qi Yu, Yu Kong

Neural pathways as model explanations consist of a sparse set of neurons that provide the same level of prediction performance as the whole model.

Uncertainty-aware State Space Transformer for Egocentric 3D Hand Trajectory Forecasting

1 code implementation ICCV 2023 Wentao Bao, Lele Chen, Libing Zeng, Zhong Li, Yi Xu, Junsong Yuan, Yu Kong

In this paper, we set up an egocentric 3D hand trajectory forecasting task that aims to predict hand trajectories in a 3D space from early observed RGB videos in a first-person view.

3D Human Pose Tracking Trajectory Forecasting

Prompting Language-Informed Distribution for Compositional Zero-Shot Learning

no code implementations23 May 2023 Wentao Bao, Lichang Chen, Heng Huang, Yu Kong

Orthogonal to the existing literature of soft, hard, or distributional prompts, our method advocates prompting the LLM-supported class distribution that leads to a better zero-shot generalization.

Compositional Zero-Shot Learning Informativeness +1

Towards Open Set Video Anomaly Detection

no code implementations23 Aug 2022 Yuansheng Zhu, Wentao Bao, Qi Yu

We develop a novel weakly supervised method for the OpenVAD problem by integrating evidential deep learning (EDL) and normalizing flows (NFs) into a multiple instance learning (MIL) framework.

Anomaly Detection Multiple Instance Learning +1

OpenTAL: Towards Open Set Temporal Action Localization

1 code implementation CVPR 2022 Wentao Bao, Qi Yu, Yu Kong

The OpenTAL is general to enable existing TAL models for open set scenarios, and experimental results on THUMOS14 and ActivityNet1. 3 benchmarks show the effectiveness of our method.

Action Classification Classification +2

Gradient Frequency Modulation for Visually Explaining Video Understanding Models

no code implementations1 Nov 2021 Xinmiao Lin, Wentao Bao, Matthew Wright, Yu Kong

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 neural networks.

Action Recognition Temporal Action Localization +1

DRIVE: Deep Reinforced Accident Anticipation with Visual Explanation

1 code implementation ICCV 2021 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 system.

Accident Anticipation Decision Making

Evidential Deep Learning for Open Set Action Recognition

2 code implementations ICCV 2021 Wentao Bao, Qi Yu, Yu Kong

Different from image data, video actions are more challenging to be recognized in an open-set setting due to the uncertain temporal dynamics and static bias of human actions.

Open Set Action Recognition Open Set Learning +1

Group Activity Prediction with Sequential Relational Anticipation Model

1 code implementation ECCV 2020 Junwen Chen, Wentao Bao, Yu Kong

Our model explicitly anticipates both activity features and positions by two graph auto-encoders, aiming to learn a discriminative group representation for group activity prediction.

Activity Prediction

Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning

2 code implementations1 Aug 2020 Wentao Bao, Qi Yu, Yu Kong

The derived uncertainty-based ranking loss is found to significantly boost model performance by improving the quality of relational features.

Accident Anticipation Activity Prediction +4

Object-Aware Centroid Voting for Monocular 3D Object Detection

no code implementations20 Jul 2020 Wentao Bao, Qi Yu, Yu Kong

Monocular 3D object detection aims to detect objects in a 3D physical world from a single camera.

Depth Estimation Monocular 3D Object Detection +3

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