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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3201–3225 of 10420 papers

TitleStatusHype
Visual Prompt Based Personalized Federated Learning—0
Task-specific Fine-tuning via Variational Information Bottleneck for Weakly-supervised Pathology Whole Slide Image ClassificationCode1
SMUG: Towards robust MRI reconstruction by smoothed unrollingCode0
A Contrastive Knowledge Transfer Framework for Model Compression and Transfer LearningCode0
Is forgetting less a good inductive bias for forward transfer?—0
Context Normalization Layer with Applications—0
Adversarial Attacks to Direct Data-driven Control for Destabilization—0
A Test Statistic Estimation-based Approach for Establishing Self-interpretable CNN-based Binary Classifiers—0
The challenge of representation learning: Improved accuracy in deep vision models does not come with better predictions of perceptual similarity—0
Twin Contrastive Learning with Noisy LabelsCode1
Bag of Tricks with Quantized Convolutional Neural Networks for image classification—0
Pretrained ViTs Yield Versatile Representations For Medical ImagesCode1
PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical DocumentsCode2
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReIDCode1
FireRisk: A Remote Sensing Dataset for Fire Risk Assessment with Benchmarks Using Supervised and Self-supervised LearningCode1
CrossFormer++: A Versatile Vision Transformer Hinging on Cross-scale AttentionCode2
On Model Compression for Neural Networks: Framework, Algorithm, and Convergence GuaranteeCode0
Schema Inference for Interpretable Image ClassificationCode1
Adv-Bot: Realistic Adversarial Botnet Attacks against Network Intrusion Detection Systems—0
Extending global-local view alignment for self-supervised learning with remote sensing imageryCode1
Endoscopy Classification Model Using Swin Transformer and Saliency Map—0
RotoGBML: Towards Out-of-Distribution Generalization for Gradient-Based Meta-Learning—0
Stabilizing Transformer Training by Preventing Attention Entropy CollapseCode2
Distributionally Robust Optimization with Probabilistic GroupCode0
Optimizing Federated Learning for Medical Image Classification on Distributed Non-iid Datasets with Partial Labels—0
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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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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
10RevCol-HTop 1 Accuracy90—Unverified