A codebase for few-shot segmentation research
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Updated
Dec 4, 2022 - Python
A codebase for few-shot segmentation research
Few-shot learning project: Semantic segmentation of COVID-19 infection in CT scans
PaddlePaddle implementation of paper "Feature-Proxy Transformer for Few-Shot Segmentation" (NeurIPS'22 Spotlight)
Segment-Like-Me: 1-shot image segmentation using Stable Diffusion
FEWSAM Few-shot Segmentation tool based on Segment Anything
Adversarially Robust Prototypical Few-shot Segmentation with Neural-ODEs
Official PyTorch Implementation of Beyond the Prototype: Divide-and-conquer Proxies for Few-shot Segmentation (IJCAI'22 Long Oral & IJCV'23).
Official PyTorch Implementation of DIaM in "A Strong Baseline for Generalized Few-Shot Semantic Segmentation" (CVPR 2023)
Official PyTorch Implementation of Holistic Prototype Activation for Few-Shot Segmentation (TPAMI'22).
This repository is the code base for the project titled Latent Embedding Optimization for Few-shot Segmentation.
PyTorch implementation of paper "Feature-Proxy Transformer for Few-Shot Segmentation" (NeurIPS'22 Spotlight)
This is the official repo for Dynamic Extension Nets for Few-shot Semantic Segmentation (ACM Multimedia 20).
Official PyTorch Implementation of Cross-Domain Few-Shot Semantic Segmentation, ECCV 2022
[AAAI 2021] (oral) Progressive One-shot Human Parsing, [TPAMI 2023] End-to-end One-shot Human Parsing
1-shot image segmentation using Stable Diffusion
Official Pytorch implementation of Multi-Similarity and Attention Guidence for Boosting Few-Shot Segmentation.
Awesome Few-shot learning
[ICCV 2021 Oral] Mining Latent Classes for Few-shot Segmentation
Official Implementation of VAT
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation (CVPR 2021)
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