ECEA: Extensible Co-Existing Attention for Few-Shot Object Detection

• Published in: IEEE transactions on image processing Vol. 33; pp. 5564 - 5576
• Main Authors: Xin, Zhimeng, Wu, Tianxu, Chen, Shiming, Zou, Yixiong, Shao, Ling, You, Xinge
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2024
• Subjects: Adaptation models; co-existing regions; Detectors; extensible attention; Feature extraction; Few-shot object detection; Object detection; Semantics; Task analysis; Training

Few-shot object detection (FSOD) identifies objects from extremely few annotated samples. Most existing FSOD methods, recently, apply the two-stage learning paradigm, which transfers the knowledge learned from abundant base classes to assist the few-shot detectors by learning the global features. Ho...