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 6776–6800 of 10420 papers

TitleStatusHype
Deep tensor networks with matrix product operators—0
Large-Scale Unsupervised Person Re-Identification with Contrastive Learning—0
Large Scale Transfer Learning for Differentially Private Image Classification—0
DeepTensor: Low-Rank Tensor Decomposition with Deep Network Priors—0
NetScore: Towards Universal Metrics for Large-scale Performance Analysis of Deep Neural Networks for Practical On-Device Edge Usage—0
Large-scale spatiotemporal photonic reservoir computer for image classification—0
Large Scale Neural Architecture Search with Polyharmonic Splines—0
Large Scale Multi-Domain Multi-Task Learning with MultiModel—0
Deep Supervision with Intermediate Concepts—0
Behavior of Mini-Batch Optimization for Training Deep Neural Networks on Large Datasets—0
Large-Scale 3D Scene Classification With Multi-View Volumetric CNN—0
Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization—0
Deep Spatial Pyramid: The Devil is Once Again in the Details—0
Large Margin Multi-modal Multi-task Feature Extraction for Image Classification—0
Large-margin Learning of Compact Binary Image Encodings—0
DeepSetNet: Predicting Sets with Deep Neural Networks—0
Neural Architecture Design and Robustness: A Dataset—0
Be Careful What You Backpropagate: A Case For Linear Output Activations & Gradient Boosting—0
An Algorithm for Routing Vectors in Sequences—0
Large Language Models Implicitly Learn to See and Hear Just By Reading—0
Neural Architecture Search for Deep Face Recognition—0
Large e-retailer image dataset for visual search and product classification—0
LARE: Latent Augmentation using Regional Embedding with Vision-Language Model—0
Deep Sequential Feature Learning in Clinical Image Classification of Infectious Keratitis—0
Language to Network: Conditional Parameter Adaptation with Natural Language Descriptions—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