Pfenet++: Boosting few-shot semantic segmentation with the noise-filtered context-aware prior mask
In this work, we revisit the prior mask guidance proposed in “Prior Guided Feature
Enrichment Network for Few-Shot Segmentation”. The prior mask serves as an indicator that …
Enrichment Network for Few-Shot Segmentation”. The prior mask serves as an indicator that …
Multi-modal prototypes for open-set semantic segmentation
In semantic segmentation, adapting a visual system to novel object categories at inference
time has always been both valuable and challenging. To enable such generalization …
time has always been both valuable and challenging. To enable such generalization …
Layer-wise mutual information meta-learning network for few-shot segmentation
The goal of few-shot segmentation (FSS) is to segment unlabeled images belonging to
previously unseen classes using only a limited number of labeled images. The main …
previously unseen classes using only a limited number of labeled images. The main …
Unlocking the Potential of Pre-trained Vision Transformers for Few-Shot Semantic Segmentation through Relationship Descriptors
The recent advent of pre-trained vision transformers has unveiled a promising property: their
inherent capability to group semantically related visual concepts. In this paper we explore to …
inherent capability to group semantically related visual concepts. In this paper we explore to …
Visual Prompting for Generalized Few-shot Segmentation: A Multi-scale Approach
The emergence of attention-based transformer models has led to their extensive use in
various tasks due to their superior generalization and transfer properties. Recent research …
various tasks due to their superior generalization and transfer properties. Recent research …
Dynamic Knowledge Adapter with Probabilistic Calibration for Generalized Few-Shot Semantic Segmentation
J Tong, H Zhou, Y Liu, Y Hu… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
Abstract Generalized Few-shot Semantic Segmentation (GFSS) aims to use a few novel-
class samples to enable the model trained on base classes to have the ability to segment for …
class samples to enable the model trained on base classes to have the ability to segment for …
Enrich Distill and Fuse: Generalized Few-Shot Semantic Segmentation in Remote Sensing Leveraging Foundation Model's Assistance
Generalized few-shot semantic segmentation (GFSS) unifies semantic segmentation with
few-shot learning showing great potential for Earth observation tasks under data scarcity …
few-shot learning showing great potential for Earth observation tasks under data scarcity …
Multi-modal prototypes for open-world semantic segmentation
In semantic segmentation, generalizing a visual system to both seen categories and novel
categories at inference time has always been practically valuable yet challenging. To enable …
categories at inference time has always been practically valuable yet challenging. To enable …
Generalized Few-Shot Meets Remote Sensing: Discovering Novel Classes in Land Cover Mapping via Hybrid Semantic Segmentation Framework
Land-cover mapping is one of the vital applications in Earth observation aiming at
classifying each pixel's land-cover type of remote-sensing images. As natural and human …
classifying each pixel's land-cover type of remote-sensing images. As natural and human …
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 …