Chuang Zhu
- LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
2021/08/24 by Xinyu Jia, Jia, Xinyu, Chuang Zhu +7 · 38 citations
Computer Science · Engineering · #Advanced Image Fusion Techniques #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Enhancement Techniques #Infrared Target Detection Methodologies
- Instance Adaptive Self-Training for Unsupervised Domain Adaptation
2020/08/27 by Ke Mei, Chuang Zhu, Mei, Ke +5 · 7 citations
Computer Science · Medicine · #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Multimodal Machine Learning Applications
- Hard-sample Guided Hybrid Contrast Learning for Unsupervised Person Re-Identification
2021/09/25 by Zheng Hu, Chuang Zhu, Hu, Zheng +3 · 1 citation
Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Gait Recognition and Analysis #Human Pose and Action Recognition #Video Surveillance and Tracking Methods
- Highly Efficient SNNs for High-speed Object Detection
2023/09/27 by Nemin Qiu, Qiu, Nemin, Zhiguo Li +5 · 1 citation
Engineering · #Advanced Memory and Neural Computing #Ferroelectric and Negative Capacitance Devices #CCD and CMOS Imaging Sensors
- Hard-aware Instance Adaptive Self-training for Unsupervised Cross-domain Semantic Segmentation
2023/02/14 by Chuang Zhu, Zhu, Chuang, Kebin Liu +9 · 1 citation
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning and Data Classification #Multimodal Machine Learning Applications
- Learning from Different Samples: A Source-free Framework for Semi-supervised Domain Adaptation
2024/11/11 by X. T. Huang, Chuang Zhu, Huang, Xinyang +5 · 1 citation
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences