| BAM (ResNet-50) |
- Mean IoU
- 51.16
- learnable parameters (million)
- 26.7
|
Learning What Not to Segment: A New Perspective on Few-Shot Segmentation 2022-03-15 |
코드 1 |
| IPRNet (ResNet-50) |
- Mean IoU
- 51.1
|
Interclass Prototype Relation for Few-Shot Segmentation 2022-11-16 |
연결 없음 |
| MCE (ResNet-50) |
- Mean IoU
- 51.04
|
Masked Cross-image Encoding for Few-shot Segmentation 2023-08-22 |
연결 없음 |
| MIANet (VGG-16) |
- Mean IoU
- 51.03
- FB-IoU
- 73.81
|
MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentation 2023-05-23 |
코드 1 |
| ASNet (HM, ResNet-101) |
- Mean IoU
- 50.6
- FB-IoU
- 73.3
|
HM: Hybrid Masking for Few-Shot Segmentation 2022-03-24 |
코드 1 |
| HSNet (HM, ResNet-101) |
- Mean IoU
- 50.6
- FB-IoU
- 72.9
|
HM: Hybrid Masking for Few-Shot Segmentation 2022-03-24 |
코드 1 |
| MSANet (ResNet-50) |
- Mean IoU
- 50.47
- FB-IoU
- 53.67
|
MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation 2022-06-20 |
코드 1 |
| SSP (ResNet-101) |
- Mean IoU
- 50.2
|
Self-Support Few-Shot Semantic Segmentation 2022-07-23 |
코드 1 |
| QCLNet (ResNet-50) |
- Mean IoU
- 50
|
Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation 2023-05-12 |
코드 1 |
| HSNet (ResNet-101) |
- Mean IoU
- 49.5
- FB-IoU
- 72.4
- learnable parameters (million)
- 2.5
|
Hypercorrelation Squeeze for Few-Shot Segmentation 2021-04-04 |
코드 1 |
| ASNet |
- Mean IoU
- 49.5
|
Integrative Few-Shot Learning for Classification and Segmentation 2022-03-29 |
코드 1 |
| PFENet (SVF, VGG-16) |
- Mean IoU
- 49.49
|
Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning 2022-06-13 |
코드 1 |
| HSNet (HM, ResNet-50) |
- Mean IoU
- 49.4
- FB-IoU
- 72.2
|
HM: Hybrid Masking for Few-Shot Segmentation 2022-03-24 |
코드 1 |
| DACM (VAT, ResNet-50) |
- Mean IoU
- 49.2
- FB-IoU
- 72.9
|
Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation 2022-07-30 |
코드 1 |
| BAM (SVF, VGG-16) |
- Mean IoU
- 49.07
|
Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning 2022-06-13 |
코드 1 |
| ASNet (HM, ResNet-50) |
- Mean IoU
- 48.4
- FB-IoU
- 72.2
|
HM: Hybrid Masking for Few-Shot Segmentation 2022-03-24 |
코드 1 |
| VAT (HM, ResNet-50) |
- Mean IoU
- 48.3
- FB-IoU
- 71.8
|
HM: Hybrid Masking for Few-Shot Segmentation 2022-03-24 |
코드 1 |
| DCAMA (ResNet-50) |
- Mean IoU
- 48.3
- FB-IoU
- 71.7
- learnable parameters (million)
- 47.7
|
Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation 2022-07-18 |
코드 1 |
| DACM (ResNet-50) |
- Mean IoU
- 48.1
- FB-IoU
- 71.6
|
Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation 2022-07-30 |
코드 1 |
| SiGCN (ResNet-50) |
- Mean IoU
- 48
- FB-IoU
- 66.2
|
Few-shot Semantic Segmentation with Support-induced Graph Convolutional Network 2023-01-09 |
연결 없음 |
| VAT (ResNet-101) |
- Mean IoU
- 47.9
- FB-IoU
- 72.4
|
Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation 2022-07-22 |
코드 1 |
| VAT (ResNet-50) |
- Mean IoU
- 47.9
|
Cost Aggregation Is All You Need for Few-Shot Segmentation 2021-12-22 |
코드 1 · 코드 2 |
| IPMT (ResNet-101) |
- Mean IoU
- 47.9
|
Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation 2022-10-13 |
코드 1 |
| FECANet (ResNet-50) |
- Mean IoU
- 47.6
- FB-IoU
- 71.1
|
FECANet: Boosting Few-Shot Semantic Segmentation with Feature-Enhanced Context-Aware Network 2023-01-19 |
코드 1 |
| IPMT (ResNet-50) |
- Mean IoU
- 47.5
|
Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation 2022-10-13 |
코드 1 |
| HSNet (ResNet-50) |
- Mean IoU
- 46.9
- FB-IoU
- 70.7
- learnable parameters (million)
- 2.5
|
Hypercorrelation Squeeze for Few-Shot Segmentation 2021-04-04 |
코드 1 |
| RePRI (CECE-M,ResNet-50) |
- Mean IoU
- 46.9
|
Clustered-patch Element Connection for Few-shot Learning 2023-04-20 |
코드 1 |
| RePRI (CECE-T,ResNet-50) |
- Mean IoU
- 46.7
|
Clustered-patch Element Connection for Few-shot Learning 2023-04-20 |
코드 1 |
| DCP (ResNet-50) |
- Mean IoU
- 46.48
|
Beyond the Prototype: Divide-and-conquer Proxies for Few-shot Segmentation 2022-04-21 |
코드 1 |
| APANet (ResNet-101) |
- Mean IoU
- 46.4
|
APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation 2021-11-24 |
연결 없음 |