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20112023
most citedDesnowNet: Context-Aware Deep Network for Snow Removal

434 citations · 1.3k across the 60 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

cs.CV2020★ 4 cited

Exploring Severe Occlusion: Multi-Person 3D Pose Estimation with Gated Convolution

Renshu Gu, Gaoang Wang, Jenq-Neng Hwang

3D human pose estimation (HPE) is crucial in many fields, such as human behavior analysis, augmented reality/virtual reality (AR/VR) applications, and self-driving industry. Videos…

cs.CV2020★ 46 cited

Traffic-Aware Multi-Camera Tracking of Vehicles Based on ReID and Camera Link Model

Hung-Min Hsu, Yizhou Wang, Jenq-Neng Hwang

Multi-target multi-camera tracking (MTMCT), i.e., tracking multiple targets across multiple cameras, is a crucial technique for smart city applications. In this paper, we propose a…

cs.CV2020

Automated Intracranial Artery Labeling using a Graph Neural Network and Hierarchical Refinement

Li Chen, Thomas Hatsukami, Jenq-Neng Hwang +1

Automatically labeling intracranial arteries (ICA) with their anatomical names is beneficial for feature extraction and detailed analysis of intracranial vascular structures. There…

cs.CV2020★ 13 cited

IA-MOT: Instance-Aware Multi-Object Tracking with Motion Consistency

Jiarui Cai, Yizhou Wang, Haotian Zhang +3

Multiple object tracking (MOT) is a crucial task in computer vision society. However, most tracking-by-detection MOT methods, with available detected bounding boxes, cannot effecti…

cs.CV2020

OVC-Net: Object-Oriented Video Captioning with Temporal Graph and Detail Enhancement

Fangyi Zhu, Jenq-Neng Hwang, Zhanyu Ma +2

Traditional video captioning requests a holistic description of the video, yet the detailed descriptions of the specific objects may not be available. Without associating the movin…

cs.CV2020

RODNet: Radar Object Detection Using Cross-Modal Supervision

Yizhou Wang, Zhongyu Jiang, Xiangyu Gao +3

Radar is usually more robust than the camera in severe driving scenarios, e.g., weak/strong lighting and bad weather. However, unlike RGB images captured by a camera, the semantic…