5 papers
YOLO-IOD: Towards Real Time Incremental Object Detection
Shizhou Zhang, Xueqiang Lv, Yinghui Xing +4
Current methods for incremental object detection (IOD) primarily rely on Faster R-CNN or DETR series detectors; however, these approaches do not accommodate the real-time YOLO dete…
DuGI-MAE: Improving Infrared Mask Autoencoders via Dual-Domain Guidance
Yinghui Xing, Xiaoting Su, Shizhou Zhang +2
Infrared imaging plays a critical role in low-light and adverse weather conditions. However, due to the distinct characteristics of infrared images, existing foundation models such…
On Modality Incomplete Infrared-Visible Object Detection: An Architecture Compatibility Perspective
Shuo Yang, Yinghui Xing, Shizhou Zhang +1
Infrared and visible object detection (IVOD) is essential for numerous around-the-clock applications. Despite notable advancements, current IVOD models exhibit notable performance…
Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector
Qirui Wu, Shizhou Zhang, De Cheng +4
Catastrophic forgetting is a critical chanllenge for incremental object detection (IOD). Most existing methods treat the detector monolithically, relying on instance replay or know…
DDF: A Novel Dual-Domain Image Fusion Strategy for Remote Sensing Image Semantic Segmentation with Unsupervised Domain Adaptation
Lingyan Ran, Lushuang Wang, Tao Zhuo +1
Semantic segmentation of remote sensing images is a challenging and hot issue due to the large amount of unlabeled data. Unsupervised domain adaptation (UDA) has proven to be advan…