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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- 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
| 📂 | Pub. | Title | Links |
|---|---|---|---|
| 📜 | PR | CDN4: A cross-view Deep Nearest Neighbor Neural Network for fine-grained few-shot classification | Paper/Code |
| 🚩 | KBS | Knowledge-driven prototype refinement for few-shot fine-grained recognition | Paper/Code |
| 📂 | Pub. | Title | Links |
|---|---|---|---|
| 📜 | MM | Channel-Spatial Support-Query Cross-Attention for Fine-Grained Few-Shot Image Classification | Paper/Code |
| 🚩 | MM | Bi-directional Task-Guided Network for Few-Shot Fine-Grained Image Classification | Paper/Code |
| 🚩 | AAAI | Cross-Layer and Cross-Sample Feature Optimization Network for Few-Shot Fine-Grained Image Classification | Paper/Code |
| 🚩 | TPAMI | Bi-Directional Ensemble Feature Reconstruction Network for Few-Shot Fine-Grained Classification | Paper/Code |
| 📜 | TIP | Angular Isotonic Loss Guided Multi-Layer Integration for Few-Shot Fine-Grained Image Classification | Paper/Code |
| 📜 | TMM | Few-shot Fine-grained Image Classification via Multi-Frequency Neighborhood and Double-cross Modulation | Paper/Code |
| 🚩 | TMM | Robust Saliency-Aware Distillation for Few-shot Fine-grained Visual Recognition | Paper/Code |
| 📜 | PR | Re-abstraction and perturbing support pair network for few-shot fine-grained image classification | Paper/Code |
| 📜 | PR | Self-reconstruction network for fine-grained few-shot classification | Paper/Code |
| 📂 | Pub. | Title | Links |
|---|---|---|---|
| 🚩 | AAAI | Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification | Paper/Code |
| 📜 | AAAI | Dual Attention Networks for Few-Shot Fine-Grained Recognition | Paper/Code |
| 🚩 | TCSVT | Boosting Few-shot Fine-grained Recognition with Background Suppression and Foreground Alignment | Paper/Code |
| 📜 | TCSVT | Locally-Enriched Cross-Reconstruction for Few-Shot Fine-Grained Image Classification | Paper/Code |
| 🚩 | arXiv | Detail Reinforcement Diffusion Model: Augmentation Fine-Grained Visual Categorization in Few-Shot Conditions | Paper/Code |
| 📂 | 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 |
| 📂 | 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 |
| 📂 | 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 |
| 📂 | 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 |
| 📂 | Pub. | Title | Links |
|---|---|---|---|
| 🚩 | MM | Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-Learning | Paper/Code |
| 📂 | Pub. | Title | Links |
|---|---|---|---|
| 🚩 | MM | M$^3$Net: Multi-view Encoding, Matching, and Fusion for Few-shot Fine-grained Action Recognition | Paper/Code |