Search Results for author: Yu Kong

Found 18 papers, 7 papers with code

GateHUB: Gated History Unit with Background Suppression for Online Action Detection

no code implementations CVPR 2022 Junwen Chen, Gaurav Mittal, Ye Yu, Yu Kong, Mei Chen

We present GateHUB, Gated History Unit with Background Suppression, that comprises a novel position-guided gated cross-attention mechanism to enhance or suppress parts of the history as per how informative they are for current frame prediction.

Online Action Detection Optical Flow Estimation

A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations

no code implementations3 Apr 2022 Krishna Prasad Neupane, Ervine Zheng, Yu Kong, Qi Yu

We present a novel dynamic recommendation model that focuses on users who have interactions in the past but turn relatively inactive recently.

Meta-Learning Recommendation Systems

Learning of Global Objective for Network Flow in Multi-Object Tracking

no code implementations CVPR 2022 Shuai Li, Yu Kong, Hamid Rezatofighi

This paper concerns the problem of multi-object tracking based on the min-cost flow (MCF) formulation, which is conventionally studied as an instance of linear program.

Association Multi-Object Tracking

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

An Eye for an Eye: Defending against Gradient-based Attacks with Gradients

no code implementations2 Feb 2022 Hanbin Hong, Yuan Hong, Yu Kong

In this paper, we show that the gradients can also be exploited as a powerful weapon to defend against adversarial attacks.

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 Video Understanding

Evidential Deep Learning for Open Set Action Recognition

1 code implementation 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

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

Explainable Video Entailment With Grounded Visual Evidence

no code implementations ICCV 2021 Junwen Chen, Yu Kong

Video entailment aims at determining if a hypothesis textual statement is entailed or contradicted by a premise video.

Visual Grounding

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 +2

Cascaded Detail-Preserving Networks for Super-Resolution of Document Images

no code implementations25 Nov 2019 Zhichao Fu, Yu Kong, Yingbin Zheng, Hao Ye, Wenxin Hu, Jing Yang, Liang He

The accuracy of OCR is usually affected by the quality of the input document image and different kinds of marred document images hamper the OCR results.

Image Super-Resolution Optical Character Recognition

Human Action Recognition and Prediction: A Survey

no code implementations28 Jun 2018 Yu Kong, Yun Fu

Derived from rapid advances in computer vision and machine learning, video analysis tasks have been moving from inferring the present state to predicting the future state.

Action Recognition Autonomous Driving +2

Residual Dense Network for Image Super-Resolution

12 code implementations CVPR 2018 Yulun Zhang, Yapeng Tian, Yu Kong, Bineng Zhong, Yun Fu

In this paper, we propose a novel residual dense network (RDN) to address this problem in image SR. We fully exploit the hierarchical features from all the convolutional layers.

Color Image Denoising Image Super-Resolution

Deep Sequential Context Networks for Action Prediction

no code implementations CVPR 2017 Yu Kong, Zhiqiang Tao, Yun Fu

Different from after-the-fact action recognition, action prediction task requires action labels to be predicted from these partially observed videos.

Action Recognition

Bilinear Heterogeneous Information Machine for RGB-D Action Recognition

no code implementations CVPR 2015 Yu Kong, Yun Fu

Rich heterogeneous RGB and depth data are effectively compressed and projected to a learned shared space, in order to reduce noise and capture useful information for recognition.

Action Recognition

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