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 4801–4850 of 10420 papers

TitleStatusHype
Combining Two Adversarial Attacks Against Person Re-Identification Systems—0
Fairness Testing of Deep Image Classification with Adequacy Metrics—0
Fairness-Aware Meta-Learning via Nash Bargaining—0
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels—0
A Residual Multi-task Network for Joint Classification and Regression in Medical Imaging—0
AdvIT: Adversarial Frames Identifier Based on Temporal Consistency in Videos—0
Fairness Analysis of CLIP-Based Foundation Models for X-Ray Image Classification—0
Combining Spiking Neural Network and Artificial Neural Network for Enhanced Image Classification—0
Fair Distillation: Teaching Fairness from Biased Teachers in Medical Imaging—0
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification—0
Are Sample-Efficient NLP Models More Robust?—0
FairDD: Fair Dataset Distillation via Synchronized Matching—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers—0
Fair Comparison: Quantifying Variance in Resultsfor Fine-grained Visual Categorization—0
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet Networks—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers—0
Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos?—0
FACTUAL: A Novel Framework for Contrastive Learning Based Robust SAR Image Classification—0
Combining pretrained CNN feature extractors to enhance clustering of complex natural images—0
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types—0
Combining multiscale features for classification of hyperspectral images: a sequence based kernel approach—0
Factorized Adversarial Networks for Unsupervised Domain Adaptation—0
Fact or Artifact? Revise Layer-wise Relevance Propagation on various ANN Architectures—0
Combining multiple resolutions into hierarchical representations for kernel-based image classification—0
Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?—0
Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches—0
A Contrastive Symmetric Forward-Forward Algorithm (SFFA) for Continual Learning Tasks—0
A Bandit Approach with Evolutionary Operators for Model Selection—0
FACET: Fairness in Computer Vision Evaluation Benchmark—0
Face Image Classification by Pooling Raw Features—0
Face Identification with Second-Order Pooling—0
Face Clustering: Representation and Pairwise Constraints—0
Creating Ensembles of Classifiers through UMDA for Aerial Scene Classification—0
Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification—0
Combining Deep Learning with Good Old-Fashioned Machine Learning—0
A Relational Model for One-Shot Classification—0
Adversarial Transformations for Semi-Supervised Learning—0
Extreme Network Compression via Filter Group Approximation—0
Combinets: Creativity via Recombination of Neural Networks—0
Extreme Learning Machines for Attention-based Multiple Instance Learning in Whole-Slide Image Classification—0
Combined Use of Federated Learning and Image Encryption for Privacy-Preserving Image Classification with Vision Transformer—0
Are Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?—0
Extrapolation Frameworks in Cognitive Psychology Suitable for Study of Image Classification Models—0
Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution—0
Combined statistical and model based texture features for improved image classification—0
Combined Scaling for Zero-shot Transfer Learning—0
Are Deep Learning Models Robust to Partial Object Occlusion in Visual Recognition Tasks?—0
Adversarial Transfer of Pose Estimation Regression—0
A Contrastive Learning Approach to Auroral Identification and Classification—0
Extracting Human Attention through Crowdsourced Patch Labeling—0
Show:102550
← PrevPage 97 of 209Next →
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