4 citations · 7 across the 5 of their papers we have counts for
6 papers
Boosting Image Super-Resolution Via Fusion of Complementary Information Captured by Multi-Modal Sensors
Fan Wang, Jiangxin Yang, Yanlong Cao +2
Image Super-Resolution (SR) provides a promising technique to enhance the image quality of low-resolution optical sensors, facilitating better-performing target detection and auton…
Learning Inter- and Intraframe Representations for Non-Lambertian Photometric Stereo
Yanlong Cao, Binjie Ding, Zewei He +4
Photometric stereo provides an important method for high-fidelity 3D reconstruction based on multiple intensity images captured under different illumination directions. In this pap…
NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
Abdelrahman Abdelhamed, Mahmoud Afifi, Radu Timofte +87
This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new versi…
Deep Neural Network for Fast and Accurate Single Image Super-Resolution via Channel-Attention-based Fusion of Orientation-aware Features
Du Chen, Zewei He, Yanpeng Cao +5
Recently, Convolutional Neural Networks (CNNs) have been successfully adopted to solve the ill-posed single image super-resolution (SISR) problem. A commonly used strategy to boost…
Unsupervised Domain Adaptation for Multispectral Pedestrian Detection
Dayan Guan, Xing Luo, Yanpeng Cao +4
Multimodal information (e.g., visible and thermal) can generate robust pedestrian detections to facilitate around-the-clock computer vision applications, such as autonomous driving…
Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pedestrian Detection
Yanpeng Cao, Dayan Guan, Yulun Wu +3
Effective fusion of complementary information captured by multi-modal sensors (visible and infrared cameras) enables robust pedestrian detection under various surveillance situatio…