SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Showing 301350 of 10419 papers

TitleStatusHype
HiFuse: Hierarchical Multi-Scale Feature Fusion Network for Medical Image ClassificationCode2
Adapter is All You Need for Tuning Visual TasksCode2
Binary Neural Networks: A SurveyCode2
Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature DistillationCode2
DAMamba: Vision State Space Model with Dynamic Adaptive ScanCode2
DEYO: DETR with YOLO for End-to-End Object DetectionCode2
Accelerating Transformers with Spectrum-Preserving Token MergingCode2
ktrain: A Low-Code Library for Augmented Machine LearningCode2
Big Transfer (BiT): General Visual Representation LearningCode2
A Survey on Mixup Augmentations and BeyondCode2
Attention Mechanisms in Computer Vision: A SurveyCode2
SCAN: Learning to Classify Images without LabelsCode2
FixMatch: Simplifying Semi-Supervised Learning with Consistency and ConfidenceCode2
LibFewShot: A Comprehensive Library for Few-shot LearningCode2
Masked Siamese Networks for Label-Efficient LearningCode2
SeaFormer++: Squeeze-enhanced Axial Transformer for Mobile Visual RecognitionCode2
CLR: Channel-wise Lightweight Reprogramming for Continual LearningCode1
Clusterability as an Alternative to Anchor Points When Learning with Noisy LabelsCode1
ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image ClassificationCode1
Counterfactual Explanations for Medical Image Classification and Regression using Diffusion AutoencoderCode1
ClusterFormer: Clustering As A Universal Visual LearnerCode1
CLIP the Gap: A Single Domain Generalization Approach for Object DetectionCode1
Spatial and Spatial-Spectral Morphological Mamba for Hyperspectral Image ClassificationCode1
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object NavigationCode1
FocusNet: Classifying Better by Focusing on Confusing ClassesCode1
Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image ClassificationCode1
CLIP4IDC: CLIP for Image Difference CaptioningCode1
CLIP-guided Federated Learning on Heterogeneous and Long-Tailed DataCode1
Clean-Label Backdoor Attacks on Video Recognition ModelsCode1
Adversarial Continual LearningCode1
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label NoiseCode1
CLIP meets DINO for Tuning Zero-Shot Classifier using Unlabeled Image CollectionsCode1
Class-Incremental Grouping Network for Continual Audio-Visual LearningCode1
Optimized spiking neurons classify images with high accuracy through temporal coding with two spikesCode1
CLCC: Contrastive Learning for Color ConstancyCode1
A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial ImagesCode1
Adversarial Example Detection for DNN Models: A Review and Experimental ComparisonCode1
Class Distance Weighted Cross-Entropy Loss for Ulcerative Colitis Severity EstimationCode1
CLCNet: Rethinking of Ensemble Modeling with Classification Confidence NetworkCode1
CMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep LearningCode1
AASAE: Augmentation-Augmented Stochastic AutoencodersCode1
A Conservative Approach for Unbiased Learning on Unknown BiasesCode1
Class-Balanced Active Learning for Image ClassificationCode1
Class-Aware Contrastive Semi-Supervised LearningCode1
Class Adaptive Network CalibrationCode1
Class-Aware Patch Embedding Adaptation for Few-Shot Image ClassificationCode1
Class-Balanced Distillation for Long-Tailed Visual RecognitionCode1
CHiLS: Zero-Shot Image Classification with Hierarchical Label SetsCode1
CheXWorld: Exploring Image World Modeling for Radiograph Representation LearningCode1
CHEX: CHannel EXploration for CNN Model CompressionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified