ljm198134 / awesome-fine-grained-few-shot-learning

The summary of code and paper for few-shot learning in fine-grained recognition

Awesome-Fine-Grained-Few-Shot-Learning

A curated list of resources including papers, datasets, and relevant links about few-shot learning in fine-grained image/video recognition. Since both few-shot and fine-grained are very broad concepts, there are various experimental settings and research lines in the realm of fine-grained few-shot learning.

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🏃 We will keep updating it, please feel free to send me a PR! 🏃
🚩 indicates some interesting or inspiring ideas

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Datasets Download

• CUB_200_2011 Dataset Page | Download Link
• FGVC-Aircraft Dataset Page | Download Link
• iNaturalist2017 Dataset Page | Download Data | Download Annotations
• Stanford-Cars Dataset Page
• Stanford-Dogs Dataset Page

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Image Classification

2023

📂	Pub.	Title	Links
🚩	AAAI	Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification	Paper/Code
🚩	TCSVT	Boosting Few-shot Fine-grained Recognition with Background Suppression and Foreground Alignment	Paper/Code

2022

📂	Pub.	Title	Links
📜	arXiv	Fine-grained Few-shot Recognition by Deep Object Parsing	Paper/Code
📜	arXiv	Few-shot Fine-grained Image Classification via Multi-Frequency Neighborhood and Double-cross Modulation	Paper/Code
🚩	MM	Learning Cross-Image Object Semantic Relation in Transformer for Few-Shot Fine-Grained Image Classification	Paper/Code
📜	AAAI	Dual Attention Networks for Few-Shot Fine-Grained Recognition	Paper/Code
🚩	CVPR	Task Discrepancy Maximization for Fine-Grained Few-Shot Classification	Paper/Code
🚩	PR	Learning Attention-Guided Pyramidal Features for Few-shot Fine-grained Recognition	Paper/Code
📜	PR	Query-Guided Networks for Few-shot Fine-grained Classification and Person Search	Paper/Code
🚩	TPAMI	Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition	Paper/Code

2021

📂	Pub.	Title	Links
📜	arXiv	NDPNet: A novel non-linear data projection network for few-shot fine-grained image classification	Paper/Code
🚩	arXiv	Compositional Fine-Grained Low-Shot Learning	Paper/Code
🚩	ICIP	Coupled Patch Similarity Network For One-Shot Fine-Grained Image Recognition	Paper/Code
🚩	ICME	Selective, Structural, Subtle: Trilinear Spatial-Awareness for Few-Shot Fine-Grained Visual Recognition	Paper/Code
🚩	CVPR	Few-Shot Classification With Feature Map Reconstruction Networks	Paper/Code
🚩	MM	Object-aware long-short-range spatial alignment for few-shot fine-grained image classification	Paper/Code
🚩	ICCV	Variational Feature Disentangling for Fine-Grained Few-Shot Classification	Paper/Code
📜	NC	Fine-grained few shot learning with foreground object transformation	Paper/Code
📜	KBS	Few-shot fine-grained classification with Spatial Attentive Comparison	Paper/Code
🚩	TPAMI	Power Normalizations in Fine-Grained Image, Few-Shot Image and Graph Classification	Paper/Code

2020

📂	Pub.	Title	Links
🚩	CVPR	Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition	Paper/Code
📜	IJCAI	Multi-attention Meta Learning for Few-shot Fine-grained Image Recognition	Paper/Code
📜	ICME	Knowledge-Based Fine-Grained Classification For Few-Shot Learning	Paper/Code
📜	TIE	Few-Shot Learning for Domain-Specific Fine-Grained Image Classification	Paper/Code
📜	TMM	Low-Rank Pairwise Alignment Bilinear Network For Few-Shot Fine-Grained Image Classification	Paper/Code
🚩	TIP	BSNet: Bi-similarity network for few-shot fine-grained image classification	Paper/Code
📜	ACL	Shaping Visual Representations with Language for Few-shot Classification	Paper/Code
🚩	NeurIPS	Compositional Zero-Shot Learning via Fine-Grained Dense Feature Composition	Paper/Code

2019

📂	Pub.	Title	Links
📜	ICME	Compare More Nuanced: Pairwise Alignment Bilinear Network for Few-Shot Fine-Grained Learning	Paper/Code
🚩	TIP	Piecewise Classifier Mappings: Learning Fine-Grained Learners for Novel Categories With Few Examples	Paper/Code

Video Classification

2021

📂	Pub.	Title	Links
🚩	MM	Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-Learning	Paper/Code