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 801–825 of 10419 papers

TitleStatusHype
Frontiers in Intelligent ColonoscopyCode2
Data Obfuscation through Latent Space Projection (LSP) for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection—0
Altogether: Image Captioning via Re-aligning Alt-text—0
KANICE: Kolmogorov-Arnold Networks with Interactive Convolutional ElementsCode0
Domain-Adaptive Pre-training of Self-Supervised Foundation Models for Medical Image Classification in Gastrointestinal EndoscopyCode0
Efficient Neural Network Training via Subset Pretraining—0
Visual Representation Learning Guided By Multi-modal Prior Knowledge—0
P-YOLOv8: Efficient and Accurate Real-Time Detection of Distracted Driving—0
AutoTrain: No-code training for state-of-the-art modelsCode7
Bayesian Concept Bottleneck Models with LLM PriorsCode0
ViMoE: An Empirical Study of Designing Vision Mixture-of-Experts—0
Open-vocabulary vs. Closed-set: Best Practice for Few-shot Object Detection Considering Text DescribabilityCode0
Visual Navigation of Digital Libraries: Retrieval and Classification of Images in the National Library of Norway's Digitised Book CollectionCode0
Reflexive Guidance: Improving OoDD in Vision-Language Models via Self-Guided Image-Adaptive Concept Generation—0
Spatial-Mamba: Effective Visual State Space Models via Structure-Aware State FusionCode2
On the Influence of Shape, Texture and Color for Learning Semantic Segmentation—0
Comparative Evaluation of Clustered Federated Learning MethodsCode0
A Hybrid Feature Fusion Deep Learning Framework for Leukemia Cancer Detection in Microscopic Blood Sample Using Gated Recurrent Unit and Uncertainty Quantification—0
How Do Training Methods Influence the Utilization of Vision Models?Code0
Reproducibility study of "LICO: Explainable Models with Language-Image Consistency"Code0
Augmentation Policy Generation for Image Classification Using Large Language Models—0
Performance of Gaussian Mixture Model Classifiers on Embedded Feature SpacesCode0
LoLDU: Low-Rank Adaptation via Lower-Diag-Upper Decomposition for Parameter-Efficient Fine-TuningCode0
Is Less More? Exploring Token Condensation as Training-free Adaptation for CLIPCode1
Interpreting and Analysing CLIP's Zero-Shot Image Classification via Mutual KnowledgeCode1
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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