Few-Shot Semantic Segmentation Network for Distinguishing Positive and Negative Examples
Few-shot segmentation (FSS) aims to segment a query image with a few support images. However, there can be large differences between images from the same category, and similarities between different categories, making it a challenging task. In addition, most FSS methods use powerful encoders to extr...
Saved in:
| Main Authors: | Feng Guo, Dong Zhou |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/7/3627 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Dual-Filter Cross Attention and Onion Pooling Network for Enhanced Few-Shot Medical Image Segmentation
by: Lina Ni, et al.
Published: (2025-03-01) -
SEMPNet: enhancing few-shot remote sensing image semantic segmentation through the integration of the segment anything model
by: Wei Ao, et al.
Published: (2024-12-01) -
Global–Local Query-Support Cross-Attention for Few-Shot Semantic Segmentation
by: Fengxi Xie, et al.
Published: (2024-09-01) -
Few-Shot Classification Study for Prototype Fusion and Completion
by: Yuheng Wang, et al.
Published: (2024-01-01) -
DSMF-Net: Dual Semantic Metric Learning Fusion Network for Few-Shot Aerial Image Semantic Segmentation
by: Xiyu Qi, et al.
Published: (2025-01-01)