activity
20192025
most citedLearning Inter- and Intraframe Representations for Non-Lambertian Photometric Stereo

24 citations · 35 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2025★ 4 cited

SC3EF: A Joint Self-Correlation and Cross-Correspondence Estimation Framework for Visible and Thermal Image Registration

Xi Tong, Xing Luo, Jiangxin Yang +1

Multispectral imaging plays a critical role in a range of intelligent transportation applications, including advanced driver assistance systems (ADAS), traffic monitoring, and nigh…

cs.CV2020★ 1 cited

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…

cs.CV2020★ 24 cited

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…

cs.CV2020

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…

eess.IV2019★ 1 cited

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…

cs.CV2019★ 4 cited

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…

cs.CV2019★ 1 cited

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…