Fine-Grained Image Classification

Fine-Grained Image Classification is a task in computer vision where the goal is to classify images into subcategories within a larger category. For example, classifying different species of birds or different types of flowers. This task is considered to be fine-grained because it requires the model to distinguish between subtle differences in visual appearance and patterns, making it more challenging than regular image classification tasks.

( Image credit: Looking for the Devil in the Details )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 101–125 of 353 papers

Title	Date	Tasks	Status	Hype	Score
Concept Learners for Few-Shot Learning	Jul 14, 2020	Few-Shot LearningFine-Grained Image Classification	CodeCode Available	1	5
Escaping the Big Data Paradigm with Compact Transformers	Apr 12, 2021	Fine-Grained Image ClassificationImage Classification	CodeCode Available	1	5
ImageNet-21K Pretraining for the Masses	Apr 22, 2021	Action RecognitionFine-Grained Image Classification	CodeCode Available	1	5
Exploration of Class Center for Fine-Grained Visual Classification	Jul 5, 2024	ClassificationFine-Grained Image Classification	CodeCode Available	1	5
Knowledge Mining with Scene Text for Fine-Grained Recognition	Mar 27, 2022	Activity RecognitionClassification	CodeCode Available	1	5
The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed Manipulation	Jan 6, 2023	BenchmarkingCrop Classification	CodeCode Available	1	5
Exploring Vision Transformers for Fine-grained Classification	Jun 19, 2021	ClassificationFine-Grained Image Classification	CodeCode Available	1	5
Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning	Jun 16, 2018	Fine-Grained Image ClassificationFine-Grained Visual Categorization	CodeCode Available	1	5
Contrastive Deep Supervision	Jul 12, 2022	Contrastive LearningFine-Grained Image Classification	CodeCode Available	1	5
Label Relation Graphs Enhanced Hierarchical Residual Network for Hierarchical Multi-Granularity Classification	Jan 10, 2022	Fine-Grained Image ClassificationRelation	CodeCode Available	1	5
ML-Decoder: Scalable and Versatile Classification Head	Nov 25, 2021	ClassificationDecoder	CodeCode Available	1	5
Learning Partial Correlation based Deep Visual Representation for Image Classification	Apr 23, 2023	Fine-Grained Image ClassificationGPU	CodeCode Available	1	5
Feature Fusion Vision Transformer for Fine-Grained Visual Categorization	Jul 6, 2021	Fine-Grained Image ClassificationFine-Grained Visual Categorization	CodeCode Available	1	5
Transformer in Transformer	Feb 27, 2021	Fine-Grained Image ClassificationImage Classification	CodeCode Available	1	5
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts	Sep 18, 2023	Fine-Grained Image ClassificationImage Classification	CodeCode Available	1	5
Learning Attentive Pairwise Interaction for Fine-Grained Classification	Feb 24, 2020	ClassificationFine-Grained Image Classification	CodeCode Available	1	5
Convolutional Fine-Grained Classification with Self-Supervised Target Relation Regularization	Aug 3, 2022	ClassificationData Augmentation	CodeCode Available	1	5
Learning Cross-Image Object Semantic Relation in Transformer for Few-Shot Fine-Grained Image Classification	Jul 2, 2022	Fine-Grained Image Classificationimage-classification	CodeCode Available	1	5
Progressive Co-Attention Network for Fine-grained Visual Classification	Jan 21, 2021	ClassificationFine-Grained Image Classification	CodeCode Available	1	5
Self-Supervised Learning by Estimating Twin Class Distributions	Oct 14, 2021	Fine-Grained Image ClassificationImage Classification	CodeCode Available	1	5
An Attention-Locating Algorithm for Eliminating Background Effects in Fine-grained Visual Classification	Jan 28, 2025	Fine-Grained Image ClassificationSpecificity	CodeCode Available	0	5
Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition	Mar 14, 2019	Fine-Grained Image ClassificationFine-Grained Image Recognition	CodeCode Available	0	5
LiT Tuned Models for Efficient Species Detection	Feb 12, 2023	Fine-Grained Image Classificationimage-classification	CodeCode Available	0	5
Correcting the Triplet Selection Bias for Triplet Loss	Sep 1, 2018	Face RecognitionFine-Grained Image Classification	CodeCode Available	0	5
Morphing Tokens Draw Strong Masked Image Models	Dec 30, 2023	Fine-Grained Image ClassificationRepresentation Learning	CodeCode Available	0	5

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All datasets Stanford Cars FGVC-Aircraft CUB-200-2011 NABirds Oxford 102 Flowers Stanford Dogs Oxford-IIIT Pets Caltech-101 Food-101 Oxford-IIIT Pet Dataset CompCars Bird-225

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	TResnet-L + PMD	Accuracy	97.3	—	Unverified
2	CMAL-Net	Accuracy	97.1	—	Unverified
3	I2-HOFI	Accuracy	96.92	—	Unverified
4	TResNet-L + ML-Decoder	Accuracy	96.41	—	Unverified
5	DAT	Accuracy	96.2	—	Unverified
6	ALIGN	Accuracy	96.13	—	Unverified
7	SR-GNN	Accuracy	96.1	—	Unverified
8	EffNet-L2 (SAM)	Accuracy	95.96	—	Unverified
9	SaSPA + CAL	Accuracy	95.72	—	Unverified
10	CAP	Accuracy	95.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	I2-HOFI	Accuracy	96.42	—	Unverified
2	SR-GNN	Accuracy	95.4	—	Unverified
3	Inceptionv4	Accuracy	95.11	—	Unverified
4	CAP	Accuracy	94.9	—	Unverified
5	CSQA-Net	Accuracy	94.7	—	Unverified
6	CMAL-Net	Accuracy	94.7	—	Unverified
7	TBMSL-Net	Accuracy	94.7	—	Unverified
8	PART	Accuracy	94.6	—	Unverified
9	SaSPA + CAL	Accuracy	94.5	—	Unverified
10	AENet	Accuracy	94.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HERBS	Accuracy	93.1	—	Unverified
2	PIM	Accuracy	92.8	—	Unverified
3	MDCM	Accuracy	92.5	—	Unverified
4	IELT	Accuracy	91.8	—	Unverified
5	CAP	Accuracy	91.8	—	Unverified
6	SFETrans	Accuracy	91.8	—	Unverified
7	SWAG (ViT H/14)	Accuracy	91.7	—	Unverified
8	ViT-NeT	Accuracy	91.7	—	Unverified
9	TransFG	Accuracy	91.7	—	Unverified
10	I2-HOFI	Accuracy	91.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HERBS	Accuracy	93	—	Unverified
2	MetaFormer (MetaFormer-2,384)	Accuracy	93	—	Unverified
3	PIM	Accuracy	92.8	—	Unverified
4	MPSA	Accuracy	92.5	—	Unverified
5	ViT-NeT (SwinV2-B)	Accuracy	92.5	—	Unverified
6	CSQA-Net	Accuracy	92.3	—	Unverified
7	I2-HOFI	Accuracy	92.12	—	Unverified
8	MDCM	Accuracy	92	—	Unverified
9	CGL	Accuracy	91.7	—	Unverified
10	SR-GNN	Accuracy	91.2	—	Unverified