4 citations · 7 across the 5 of their papers we have counts for
5 papers
CSCNET: Class-Specified Cascaded Network for Compositional Zero-Shot Learning
Yanyi Zhang, Qi Jia, Xin Fan +2
Attribute and object (A-O) disentanglement is a fundamental and critical problem for Compositional Zero-shot Learning (CZSL), whose aim is to recognize novel A-O compositions based…
Diving into Darkness: A Dual-Modulated Framework for High-Fidelity Super-Resolution in Ultra-Dark Environments
Jiaxin Gao, Ziyu Yue, Yaohua Liu +3
Super-resolution tasks oriented to images captured in ultra-dark environments is a practical yet challenging problem that has received little attention. Due to uneven illumination…
Trash to Treasure: Low-Light Object Detection via Decomposition-and-Aggregation
Xiaohan Cui, Long Ma, Tengyu Ma +3
Object detection in low-light scenarios has attracted much attention in the past few years. A mainstream and representative scheme introduces enhancers as the pre-processing for re…
AdvMono3D: Advanced Monocular 3D Object Detection with Depth-Aware Robust Adversarial Training
Xingyuan Li, Jinyuan Liu, Long Ma +2
Monocular 3D object detection plays a pivotal role in the field of autonomous driving and numerous deep learning-based methods have made significant breakthroughs in this area. Des…
Enhancing Infrared Small Target Detection Robustness with Bi-Level Adversarial Framework
Zhu Liu, Zihang Chen, Jinyuan Liu +3
The detection of small infrared targets against blurred and cluttered backgrounds has remained an enduring challenge. In recent years, learning-based schemes have become the mainst…