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cs.CV2024
AFANet: Adaptive Frequency-Aware Network for Weakly-Supervised Few-Shot Semantic Segmentation
Jiaqi Ma, Guo-Sen Xie, Fang Zhao +1
Few-shot learning aims to recognize novel concepts by leveraging prior knowledge learned from a few samples. However, for visually intensive tasks such as few-shot semantic segment…
cs.CV2024
Kernel-Aware Graph Prompt Learning for Few-Shot Anomaly Detection
Fenfang Tao, Guo-Sen Xie, Fang Zhao +1
Few-shot anomaly detection (FSAD) aims to detect unseen anomaly regions with the guidance of very few normal support images from the same class. Existing FSAD methods usually find…