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

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Showing 651–700 of 10419 papers

TitleStatusHype
CODE-CL: Conceptor-Based Gradient Projection for Deep Continual LearningCode1
CoDeNet: Efficient Deployment of Input-Adaptive Object Detection on Embedded FPGAsCode1
AMC-Loss: Angular Margin Contrastive Loss for Improved Explainability in Image ClassificationCode1
Adaptive DropBlock Enhanced Generative Adversarial Networks for Hyperspectral Image ClassificationCode1
Combining Metric Learning and Attention Heads For Accurate and Efficient Multilabel Image ClassificationCode1
Communication-Efficient and Privacy-Preserving Feature-based Federated Transfer LearningCode1
Adaptive Edge Offloading for Image Classification Under Rate LimitCode1
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge DistillationCode1
An Enhanced Scheme for Reducing the Complexity of Pointwise Convolutions in CNNs for Image Classification Based on Interleaved Grouped Filters without Divisibility ConstraintsCode1
Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural NetworkCode1
Compressing Features for Learning with Noisy LabelsCode1
Compressive Visual RepresentationsCode1
An Ensemble of Simple Convolutional Neural Network Models for MNIST Digit RecognitionCode1
CondenseNet V2: Sparse Feature Reactivation for Deep NetworksCode1
Confidence-aware multi-modality learning for eye disease screeningCode1
Confidence Regularized Self-TrainingCode1
A Neural Dirichlet Process Mixture Model for Task-Free Continual LearningCode1
Container: Context Aggregation NetworkCode1
Domain Prompt Learning for Efficiently Adapting CLIP to Unseen DomainsCode1
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object NavigationCode1
A New Semi-supervised Learning Benchmark for Classifying View and Diagnosing Aortic Stenosis from EchocardiogramsCode1
FocusNet: Classifying Better by Focusing on Confusing ClassesCode1
A New Benchmark: On the Utility of Synthetic Data with Blender for Bare Supervised Learning and Downstream Domain AdaptationCode1
Continual Learning for LiDAR Semantic Segmentation: Class-Incremental and Coarse-to-Fine strategies on Sparse DataCode1
Adaptive Mask Sampling and Manifold to Euclidean Subspace Learning with Distance Covariance Representation for Hyperspectral Image ClassificationCode1
ConTNet: Why not use convolution and transformer at the same time?Code1
CMW-Net: Learning a Class-Aware Sample Weighting Mapping for Robust Deep LearningCode1
Contrastive Learning Improves Model Robustness Under Label NoiseCode1
Combining Human Predictions with Model Probabilities via Confusion Matrices and CalibrationCode1
Continual atlas-based segmentation of prostate MRICode1
Contrastive Masked Autoencoders are Stronger Vision LearnersCode1
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy LabelsCode1
ConvMLP: Hierarchical Convolutional MLPs for VisionCode1
Convolutional Channel-wise Competitive Learning for the Forward-Forward AlgorithmCode1
Convolutional Spiking Neural Networks for Spatio-Temporal Feature ExtractionCode1
Convolutional Xformers for VisionCode1
Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised LearningCode1
Deeply Coupled Cross-Modal Prompt LearningCode1
Counterfactual Visual ExplanationsCode1
COVID-CXNet: Detecting COVID-19 in Frontal Chest X-ray Images using Deep LearningCode1
Achieving Fairness Through Channel Pruning for Dermatological Disease DiagnosisCode1
Can An Image Classifier Suffice For Action Recognition?Code1
CLCC: Contrastive Learning for Color ConstancyCode1
Cross-Domain Ensemble Distillation for Domain GeneralizationCode1
Class-Incremental Grouping Network for Continual Audio-Visual LearningCode1
An In-depth Study of Stochastic BackpropagationCode1
Adaptive Risk Minimization: Learning to Adapt to Domain ShiftCode1
Cross-Layer Retrospective Retrieving via Layer AttentionCode1
CLCNet: Rethinking of Ensemble Modeling with Classification Confidence NetworkCode1
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODECode1
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified