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 5851–5875 of 10420 papers

TitleStatusHype
Learning to Generate Synthetic Training Data using Gradient Matching and Implicit DifferentiationCode0
Is it all a cluster game? -- Exploring Out-of-Distribution Detection based on Clustering in the Embedding Space—0
One Network Doesn't Rule Them All: Moving Beyond Handcrafted Architectures in Self-Supervised Learning—0
2-speed network ensemble for efficient classification of incremental land-use/land-cover satellite image chips—0
Towards understanding deep learning with the natural clustering prior—0
InsCon:Instance Consistency Feature Representation via Self-Supervised Learning—0
Generalized but not Robust? Comparing the Effects of Data Modification Methods on Out-of-Domain Generalization and Adversarial Robustness—0
Meta Ordinal Regression Forest for Medical Image Classification with Ordinal Labels—0
On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency—0
Cross-View-Prediction: Exploring Contrastive Feature for Hyperspectral Image Classification—0
UniVIP: A Unified Framework for Self-Supervised Visual Pre-training—0
Scaling the Wild: Decentralizing Hogwild!-style Shared-memory SGDCode0
GSDA: Generative Adversarial Network-based Semi-Supervised Data Augmentation for Ultrasound Image Classification—0
Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations—0
Sparse Subspace Clustering for Concept Discovery (SSCCD)—0
Learning from Attacks: Attacking Variational Autoencoder for Improving Image Classification—0
Multiscale Convolutional Transformer with Center Mask Pretraining for Hyperspectral Image Classification—0
Renyi Fair Information Bottleneck for Image Classification—0
Active Self-Semi-Supervised Learning for Few Labeled Samples—0
Uni4Eye: Unified 2D and 3D Self-supervised Pre-training via Masked Image Modeling Transformer for Ophthalmic Image Classification—0
Dynamic Group Transformer: A General Vision Transformer Backbone with Dynamic Group Attention—0
Discriminability-Transferability Trade-Off: An Information-Theoretic PerspectiveCode0
Art-Attack: Black-Box Adversarial Attack via Evolutionary Art—0
Explaining Classifiers by Constructing Familiar ConceptsCode0
Dynamic ConvNets on Tiny Devices via Nested Sparsity—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
10RevCol-HTop 1 Accuracy90—Unverified