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 6001–6025 of 10420 papers

TitleStatusHype
LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations—0
Locality Guided Neural Networks for Explainable Artificial Intelligence—0
Localization-Aware Active Learning for Object Detection—0
Localized Adversarial Training for Increased Accuracy and Robustness in Image Classification—0
Localizing Interpretable Multi-scale informative Patches Derived from Media Classification Task—0
Lensless-camera based machine learning for image classification—0
LeDNet: Localization-enabled Deep Neural Network for Multi-Label Radiography Image Classification—0
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning—0
Learn to Predict Sets Using Feed-Forward Neural Networks—0
Locally Differentially Private Gradient Tracking for Distributed Online Learning over Directed Graphs—0
DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification—0
BigEarthNet-MM: A Large Scale Multi-Modal Multi-Label Benchmark Archive for Remote Sensing Image Classification and Retrieval—0
An Attention Module for Convolutional Neural Networks—0
A Dataset and Benchmarks for Multimedia Social Analysis—0
A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification—0
2-speed network ensemble for efficient classification of incremental land-use/land-cover satellite image chips—0
1D-Convolutional Capsule Network for Hyperspectral Image Classification—0
LoCa: Logit Calibration for Knowledge Distillation—0
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification—0
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention—0
DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning—0
Learning with Recursive Perceptual Representations—0
Learning with Noisy Ground Truth: From 2D Classification to 3D Reconstruction—0
DevNet: A Deep Event Network for Multimedia Event Detection and Evidence Recounting—0
Anatomy-specific classification of medical images using deep convolutional nets—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