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 76–100 of 353 papers

Title	Date	Tasks	Status	Hype
Leaf Cultivar Identification via Prototype-enhanced Learning	May 5, 2023	Fine-Grained Image Classification	—Unverified	0
Reduction of Class Activation Uncertainty with Background Information	May 5, 2023	ClassificationFine-Grained Image Classification	CodeCode Available	1
PVP: Pre-trained Visual Parameter-Efficient Tuning	Apr 26, 2023	Fine-Grained Image ClassificationImage Classification	—Unverified	0
Learning Partial Correlation based Deep Visual Representation for Image Classification	Apr 23, 2023	Fine-Grained Image ClassificationGPU	CodeCode Available	1
DINOv2: Learning Robust Visual Features without Supervision	Apr 14, 2023	Depth EstimationDomain Generalization	CodeCode Available	6
Your Diffusion Model is Secretly a Zero-Shot Classifier	Mar 28, 2023	Domain GeneralizationFine-Grained Image Classification	CodeCode Available	2
Take 5: Interpretable Image Classification with a Handful of Features	Mar 23, 2023	DiversityFine-Grained Image Classification	CodeCode Available	1
Learn from Each Other to Classify Better: Cross-layer Mutual Attention Learning for Fine-grained Visual Classification	Mar 22, 2023	Fine-Grained Image Classification	CodeCode Available	1
Cascading Hierarchical Networks with Multi-task Balanced Loss for Fine-grained hashing	Mar 20, 2023	Data AugmentationFine-Grained Image Classification	CodeCode Available	0
Fine-grained Visual Classification with High-temperature Refinement and Background Suppression	Mar 11, 2023	Fine-Grained Image ClassificationVocal Bursts Intensity Prediction	CodeCode Available	1
Semantic Feature Integration network for Fine-grained Visual Classification	Feb 13, 2023	ClassificationFine-Grained Image Classification	—Unverified	0
Fine-Grained Visual Classification via Internal Ensemble Learning Transformer	Feb 13, 2023	ClassificationEnsemble Learning	CodeCode Available	1
How to Use Dropout Correctly on Residual Networks with Batch Normalization	Feb 13, 2023	ClassificationFine-Grained Image Classification	CodeCode Available	0
LiT Tuned Models for Efficient Species Detection	Feb 12, 2023	Fine-Grained Image Classificationimage-classification	CodeCode Available	0
On the Ideal Number of Groups for Isometric Gradient Propagation	Feb 7, 2023	Fine-Grained Image ClassificationImage Classification	—Unverified	0
The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed Manipulation	Jan 6, 2023	BenchmarkingCrop Classification	CodeCode Available	1
Multi-View Active Fine-Grained Visual Recognition	Jan 1, 2023	Fine-Grained Image ClassificationFine-Grained Visual Recognition	CodeCode Available	0
An Erudite Fine-Grained Visual Classification Model	Jan 1, 2023	ClassificationDisentanglement	—Unverified	0
TransIFC: Invariant Cues-aware Feature Concentration Learning for Efficient Fine-grained Bird Image Classification	Dec 31, 2022	feature selectionFine-Grained Image Classification	—Unverified	0
Part-guided Relational Transformers for Fine-grained Visual Recognition	Dec 28, 2022	Fine-Grained Image ClassificationFine-Grained Visual Recognition	CodeCode Available	1
Towards Scene Understanding for Autonomous Operations on Airport Aprons	Dec 4, 2022	Autonomous DrivingBenchmarking	CodeCode Available	1
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification	Nov 30, 2022	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
Data Augmentation Vision Transformer for Fine-grained Image Classification	Nov 23, 2022	ClassificationData Augmentation	—Unverified	0
Penalizing the Hard Example But Not Too Much: A Strong Baseline for Fine-Grained Visual Classification	Nov 21, 2022	Fine-Grained Image ClassificationFine-Grained Visual Recognition	CodeCode Available	1
2nd Place Solution to Google Universal Image Embedding	Oct 17, 2022	Fine-Grained Image Classificationimage-classification	CodeCode Available	1

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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	TransFG	Accuracy	91.7	—	Unverified
8	ViT-NeT	Accuracy	91.7	—	Unverified
9	SWAG (ViT H/14)	Accuracy	91.7	—	Unverified
10	FFVT	Accuracy	91.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MetaFormer (MetaFormer-2,384)	Accuracy	93	—	Unverified
2	HERBS	Accuracy	93	—	Unverified
3	PIM	Accuracy	92.8	—	Unverified
4	ViT-NeT (SwinV2-B)	Accuracy	92.5	—	Unverified
5	MPSA	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