Few-Shot Semantic Segmentation

39 papers with code • 12 benchmarks • 2 datasets

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Use these libraries to find Few-Shot Semantic Segmentation models and implementations

Most implemented papers

PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment

kaixin96/PANet ICCV 2019

In this paper, we tackle the challenging few-shot segmentation problem from a metric learning perspective and present PANet, a novel prototype alignment network to better utilize the information of the support set.

Prior Guided Feature Enrichment Network for Few-Shot Segmentation

Jia-Research-Lab/PFENet 4 Aug 2020

It consists of novel designs of (1) a training-free prior mask generation method that not only retains generalization power but also improves model performance and (2) Feature Enrichment Module (FEM) that overcomes spatial inconsistency by adaptively enriching query features with support features and prior masks.

Part-aware Prototype Network for Few-shot Semantic Segmentation

Xiangyi1996/PPNet-PyTorch ECCV 2020

In this paper, we propose a novel few-shot semantic segmentation framework based on the prototype representation.

Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?

mboudiaf/RePRI-for-Few-Shot-Segmentation CVPR 2021

We show that the way inference is performed in few-shot segmentation tasks has a substantial effect on performances -- an aspect often overlooked in the literature in favor of the meta-learning paradigm.

Few-Shot Segmentation via Cycle-Consistent Transformer

GengDavid/CyCTR NeurIPS 2021

Directly performing cross-attention may aggregate these features from support to query and bias the query features.

Cost Aggregation Is All You Need for Few-Shot Segmentation

Seokju-Cho/Volumetric-Aggregation-Transformer 22 Dec 2021

We introduce a novel cost aggregation network, dubbed Volumetric Aggregation with Transformers (VAT), to tackle the few-shot segmentation task by using both convolutions and transformers to efficiently handle high dimensional correlation maps between query and support.

A dense subgraph based algorithm for compact salient image region detection

sourachakra/densesubgraphsaliency 20 Nov 2015

We present an algorithm for graph based saliency computation that utilizes the underlying dense subgraphs in finding visually salient regions in an image.

SG-One: Similarity Guidance Network for One-Shot Semantic Segmentation

xiaomengyc/SG-One 22 Oct 2018

In this way, the possibilities embedded in the produced similarity maps can be adapted to guide the process of segmenting objects.

Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning

arnab39/FewShot_GAN-Unet3D 29 Oct 2018

In addition, our work presents a comprehensive analysis of different GAN architectures for semi-supervised segmentation, showing recent techniques like feature matching to yield a higher performance than conventional adversarial training approaches.