Few-Shot Image Classification

Few-Shot Image Classification is a computer vision task that involves training machine learning models to classify images into predefined categories using only a few labeled examples of each category (typically ( Image credit: Learning Embedding Adaptation for Few-Shot Learning )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 101–150 of 353 papers

Title	Date	Tasks	Status	Hype	Score
Constellation Nets for Few-Shot Learning	Jan 1, 2021	ClusteringFew-Shot Image Classification	CodeCode Available	1	5
Universal Representation Learning from Multiple Domains for Few-shot Classification	Mar 25, 2021	ClassificationFew-Shot Image Classification	CodeCode Available	1	5
PanGu-α: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation	Apr 26, 2021	Cloze (multi-choices) (Few-Shot)Cloze (multi-choices) (One-Shot)	CodeCode Available	1	5
Meta-Learning with Differentiable Convex Optimization	Apr 7, 2019	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Context-Aware Meta-Learning	Oct 17, 2023	Few-Shot Image ClassificationIn-Context Learning	CodeCode Available	1	5
Meta-Learning with a Geometry-Adaptive Preconditioner	Apr 4, 2023	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification	Jun 20, 2022	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Meta-Learning with Implicit Gradients	Sep 10, 2019	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Meta-Transfer Learning for Few-Shot Learning	Dec 6, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions	Dec 10, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Few-Shot Image Classification Benchmarks are Too Far From Reality: Build Back Better with Semantic Task Sampling	May 10, 2022	Few-Shot Image ClassificationGeneral Classification	CodeCode Available	1	5
Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple Classifier	Jan 3, 2021	ClassificationCross-Domain Few-Shot	CodeCode Available	1	5
Multistage Relation Network With Dual-Metric for Few-Shot Hyperspectral Image Classification	Apr 28, 2023	ClassificationFew-Shot Image Classification	CodeCode Available	1	5
On sensitivity of meta-learning to support data	Oct 26, 2021	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML	Sep 19, 2019	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation	Oct 30, 2019	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Few-Shot Learning by Integrating Spatial and Frequency Representation	May 11, 2021	ClassificationFew-Shot Image Classification	CodeCode Available	1	5
How to train your MAML	Oct 22, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification	Nov 30, 2022	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
On First-Order Meta-Learning Algorithms	Mar 8, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Few-shot Relational Reasoning via Connection Subgraph Pretraining	Oct 13, 2022	Few-Shot Image ClassificationMeta-Learning	CodeCode Available	1	5
FewVS: A Vision-Semantics Integration Framework for Few-Shot Image Classification	Oct 28, 2024	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions	May 27, 2022	BenchmarkingFew-Shot Image Classification	CodeCode Available	1	5
Few-Shot Classification with Feature Map Reconstruction Networks	Dec 2, 2020	ClassificationCross-Domain Few-Shot	CodeCode Available	1	5
Debiased Learning from Naturally Imbalanced Pseudo-Labels	Jan 5, 2022	counterfactualCounterfactual Reasoning	CodeCode Available	1	5
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks	Oct 1, 2018	3D Shape RecognitionDecoder	CodeCode Available	1	5
Transductive Zero-Shot and Few-Shot CLIP	Jan 1, 2024	ClassificationFew-Shot Image Classification	CodeCode Available	1	5
Generalized Few-Shot Video Classification with Video Retrieval and Feature Generation	Jul 9, 2020	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Assessing Sample Quality via the Latent Space of Generative Models	Jul 21, 2024	Few-Shot Image Classificationimage-classification	CodeCode Available	0	5
Neural TMDlayer: Modeling Instantaneous flow of features via SDE Generators	Aug 19, 2021	Data AugmentationFew-Shot Image Classification	CodeCode Available	0	5
Data-Efficient Language Shaped Few-shot Image Classification	Nov 1, 2021	ClassificationFew-Shot Image Classification	CodeCode Available	0	5
Few-Shot Learning with Global Class Representations	Aug 14, 2019	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0	5
Curriculum Meta-Learning for Few-shot Classification	Dec 6, 2021	ClassificationFew-Shot Image Classification	CodeCode Available	0	5
Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-Learning	Oct 25, 2021	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0	5
Few-Shot Learning for Image Classification of Common Flora	May 7, 2021	ClassificationFew-Shot Image Classification	CodeCode Available	0	5
Support-Set Context Matters for Bongard Problems	Sep 7, 2023	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0	5
Few-Shot Image Recognition by Predicting Parameters from Activations	Jun 12, 2017	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0	5
Image Deformation Meta-Networks for One-Shot Learning	May 28, 2019	Few-Shot Image ClassificationMeta-Learning	CodeCode Available	0	5
Amortized Bayesian Meta-Learning	May 1, 2019	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0	5
Cooperative Meta-Learning with Gradient Augmentation	Jun 7, 2024	Few-Shot Image Classificationimage-classification	CodeCode Available	0	5
Multi-level Metric Learning for Few-shot Image Recognition	Mar 21, 2021	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0	5
Multi-level Second-order Few-shot Learning	Jan 15, 2022	Action RecognitionFew-Shot action recognition	CodeCode Available	0	5
Meta-Learning without Memorization	Dec 9, 2019	Few-Shot Image Classificationimage-classification	CodeCode Available	0	5
A Simple Neural Attentive Meta-Learner	Jul 11, 2017	Few-Shot Image ClassificationMeta-Learning	CodeCode Available	0	5
A Simple Approach to Adversarial Robustness in Few-shot Image Classification	Apr 11, 2022	Adversarial RobustnessFew-Shot Image Classification	CodeCode Available	0	5
Few and Fewer: Learning Better from Few Examples Using Fewer Base Classes	Jan 29, 2024	Cross-Domain Few-ShotFew-Shot Image Classification	CodeCode Available	0	5
Contextualizing Meta-Learning via Learning to Decompose	Jun 15, 2021	AttributeFew-Shot Image Classification	CodeCode Available	0	5
Meta-Learning Probabilistic Inference For Prediction	May 24, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0	5
Multidimensional Belief Quantification for Label-Efficient Meta-Learning	Mar 23, 2022	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0	5
MetaFun: Meta-Learning with Iterative Functional Updates	Dec 5, 2019	DecoderFew-Shot Image Classification	CodeCode Available	0	5

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All datasets Mini-Imagenet 5-way (1-shot)Mini-Imagenet 5-way (5-shot)Tiered ImageNet 5-way (5-shot)Tiered ImageNet 5-way (1-shot)CIFAR-FS 5-way (5-shot)CIFAR-FS 5-way (1-shot)CUB 200 5-way 1-shot CUB 200 5-way 5-shot FC100 5-way (1-shot)FC100 5-way (5-shot)Meta-Dataset OMNIGLOT - 1-Shot, 20-way

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SgVA-CLIP	Accuracy	97.95	—	Unverified
2	CAML [Laion-2b]	Accuracy	96.2	—	Unverified
3	P>M>F (P=DINO-ViT-base, M=ProtoNet)	Accuracy	95.3	—	Unverified
4	TRIDENT	Accuracy	86.11	—	Unverified
5	PT+MAP+SF+SOT (transductive)	Accuracy	85.59	—	Unverified
6	PT+MAP+SF+BPA (transductive)	Accuracy	85.59	—	Unverified
7	PEMnE-BMS* (transductive)	Accuracy	85.54	—	Unverified
8	PT+MAP (s+f) (transductive)	Accuracy	84.81	—	Unverified
9	BAVARDAGE	Accuracy	84.8	—	Unverified
10	EASY 3xResNet12 (transductive)	Accuracy	84.04	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SgVA-CLIP	Accuracy	98.72	—	Unverified
2	CAML [Laion-2b]	Accuracy	98.6	—	Unverified
3	P>M>F (P=DINO-ViT-base, M=ProtoNet)	Accuracy	98.4	—	Unverified
4	TRIDENT	Accuracy	95.95	—	Unverified
5	BAVARDAGE	Accuracy	91.65	—	Unverified
6	PEMnE-BMS*(transductive)	Accuracy	91.53	—	Unverified
7	Transductive CNAPS + FETI	Accuracy	91.5	—	Unverified
8	PT+MAP+SF+BPA (transductive)	Accuracy	91.34	—	Unverified
9	PT+MAP+SF+SOT (transductive)	Accuracy	91.34	—	Unverified
10	AmdimNet	Accuracy	90.98	—	Unverified