RPMG-FSS: Robust prior mask guided few-shot semantic segmentation
Few-shot semantic segmentation (FSS) has been developed to perform pixel-level
segmentation with only a few dense labeled examples for training, which relieves the …
segmentation with only a few dense labeled examples for training, which relieves the …
QGRL: quaternion graph representation learning for heterogeneous feature data clustering
Clustering is one of the most commonly used techniques for unsupervised data analysis. As
real data sets are usually composed of numerical and categorical features that are …
real data sets are usually composed of numerical and categorical features that are …
Mask-guided correlation learning for few-shot segmentation in remote sensing imagery
Few-shot segmentation aims to segment specific objects in a query image based on a few
densely annotated images and has been extensively studied in recent years. In remote …
densely annotated images and has been extensively studied in recent years. In remote …
Break the bias: Delving semantic transform invariance for few-shot segmentation
Few-shot semantic segmentation (FSS) aims to segment objects of unseen classes in query
images with only a few annotated support images. Existing FSS algorithms typically focus on …
images with only a few annotated support images. Existing FSS algorithms typically focus on …
Psanet: prototype-guided salient attention for few-shot segmentation
Few-shot semantic segmentation aims to learn a generalized model for unseen-class
segmentation with just a few densely annotated samples. Most current metric-based …
segmentation with just a few densely annotated samples. Most current metric-based …
DRNet: Disentanglement and recombination network for few-shot semantic segmentation
Z Chang, X Gao, N Li, H Zhou… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Few-shot semantic segmentation (FSS) aims to segment novel classes with only a few
annotated samples. Existing methods to FSS generally combine the annotated mask and the …
annotated samples. Existing methods to FSS generally combine the annotated mask and the …
EFTNet: an efficient fine-tuning method for few-shot segmentation
J Li, Y Wang, Z Gao, Y Wei - Applied Intelligence, 2024 - Springer
Few-shot segmentation (FSS) aims to segment novel classes given a small number of
labeled samples. Most of the existing studies do not fine-tune the model during meta-testing …
labeled samples. Most of the existing studies do not fine-tune the model during meta-testing …
Few-shot semantic segmentation via multi-level feature extraction and multi-prototype localization
H Zhu, J Wang, Y Zhou, Z Gao, L Zhang - Multimedia Tools and …, 2024 - Springer
Abstract Few-shot Semantic Segmentation (FSS) segments query images only by using a
few support images with ground truth. The existing methods usually extract a single …
few support images with ground truth. The existing methods usually extract a single …
QEAN: quaternion-enhanced attention network for visual dance generation
Z Zhou, Y Huo, G Huang, A Zeng, X Chen, L Huang… - The Visual …, 2024 - Springer
The study of music-generated dance is a novel and challenging image generation task. It
aims to input a piece of music and seed motions, then generate natural dance movements …
aims to input a piece of music and seed motions, then generate natural dance movements …
Weakly supervised semantic segmentation via saliency perception with uncertainty-guided noise suppression
Abstract Weakly Supervised Semantic Segmentation (WSSS) has become increasingly
popular for achieving remarkable segmentation with only image-level labels. Current WSSS …
popular for achieving remarkable segmentation with only image-level labels. Current WSSS …