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 18511875 of 10419 papers

TitleStatusHype
CLIP meets DINO for Tuning Zero-Shot Classifier using Unlabeled Image CollectionsCode1
Robust Semantic Interpretability: Revisiting Concept Activation VectorsCode1
Dendritic Learning-incorporated Vision Transformer for Image RecognitionCode1
Deep Transferring QuantizationCode1
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object NavigationCode1
Shredder: Learning Noise Distributions to Protect Inference PrivacyCode1
SSR: An Efficient and Robust Framework for Learning with Unknown Label NoiseCode1
A Fuzzy Rank-based Ensemble of CNN Models for Classification of Cervical CytologyCode1
UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue SegmentationCode1
CLIP the Gap: A Single Domain Generalization Approach for Object DetectionCode1
SafeML: Safety Monitoring of Machine Learning Classifiers through Statistical Difference MeasureCode1
SageMix: Saliency-Guided Mixup for Point CloudsCode1
Deep Subdomain Adaptation Network for Image ClassificationCode1
SAM-MIL: A Spatial Contextual Aware Multiple Instance Learning Approach for Whole Slide Image ClassificationCode1
SAR Image Classification Based on Spiking Neural Network through Spike-Time Dependent Plasticity and Gradient DescentCode1
Scalable and Practical Natural Gradient for Large-Scale Deep LearningCode1
A fuzzy distance-based ensemble of deep models for cervical cancer detectionCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
Deep Unlearning: Fast and Efficient Gradient-free Approach to Class ForgettingCode1
Clusterability as an Alternative to Anchor Points When Learning with Noisy LabelsCode1
Deep Roto-Translation Scattering for Object ClassificationCode1
Deep Semantic Dictionary Learning for Multi-label Image ClassificationCode1
Co^2L: Contrastive Continual LearningCode1
A Fully Tensorized Recurrent Neural NetworkCode1
Deep Reinforcement Learning for Band Selection in Hyperspectral Image ClassificationCode1
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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