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 4826–4850 of 10420 papers

TitleStatusHype
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
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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