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 10226–10250 of 10420 papers

TitleStatusHype
Unsupervised Video Analysis Based on a Spatiotemporal Saliency Detector—0
Boosting Convolutional Features for Robust Object Proposals—0
A General Framework for Multi-focal Image Classification and Authentication: Application to Microscope Pollen Images—0
Enhanced Image Classification With a Fast-Learning Shallow Convolutional Neural Network—0
Hybrid multi-layer Deep CNN/Aggregator feature for image classification—0
Exploiting Image-trained CNN Architectures for Unconstrained Video Classification—0
Training Binary Multilayer Neural Networks for Image Classification using Expectation BackpropagationCode0
Fully Connected Deep Structured Networks—0
Color Image Classification via Quaternion Principal Component Analysis Network—0
Temporal Pyramid Pooling Based Convolutional Neural Networks for Action Recognition—0
Modelling Local Deep Convolutional Neural Network Features to Improve Fine-Grained Image Classification—0
Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval—0
Scalable Bayesian Optimization Using Deep Neural NetworksCode0
Invariant backpropagation: how to train a transformation-invariant neural networkCode0
Learning Transferable Features with Deep Adaptation NetworksCode0
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification—0
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet ClassificationCode0
Multimodal Task-Driven Dictionary Learning for Image ClassificationCode0
Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Probe and Learn Neural Networks—0
Deep Boosting: Layered Feature Mining for General Image Classification—0
DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification—0
Task-Driven Dictionary Learning for Hyperspectral Image Classification with Structured Sparsity Constraints—0
Dynamic texture and scene classification by transferring deep image features—0
Multi-task Image Classification via Collaborative, Hierarchical Spike-and-Slab Priors—0
Vector Quantization by Minimizing Kullback-Leibler Divergence—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
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