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 3101–3125 of 10420 papers

TitleStatusHype
Source-free Domain Adaptation Requires Penalized Diversity—0
Patch-wise Features for Blur Image Classification—0
Robust Neural Architecture Search—0
Adopting Two Supervisors for Efficient Use of Large-Scale Remote Deep Neural NetworksCode0
High-fidelity Pseudo-labels for Boosting Weakly-Supervised SegmentationCode0
SMPConv: Self-moving Point Representations for Continuous ConvolutionCode1
Self-Supervised Siamese Autoencoders—0
A Certified Radius-Guided Attack Framework to Image Segmentation ModelsCode0
Efficient CNNs via Passive Filter Pruning—0
Context-Aware Classification of Legal Document Pages—0
Adaptive Ensemble Learning: Boosting Model Performance through Intelligent Feature Fusion in Deep Neural Networks—0
Uncertainty estimation in Deep Learning for Panoptic segmentation—0
Multi-Class Unlearning for Image Classification via Weight Filtering—0
EGC: Image Generation and Classification via a Diffusion Energy-Based ModelCode1
Learning to Name Classes for Vision and Language Models—0
VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue DistributionCode1
Strong Baselines for Parameter Efficient Few-Shot Fine-tuning—0
Cross-modulated Few-shot Image Generation for Colorectal Tissue ClassificationCode1
Astroformer: More Data Might not be all you need for ClassificationCode1
Online Algorithms for Hierarchical Inference in Deep Learning applications at the Edge—0
Knowledge Accumulation in Continually Learned Representations and the Issue of Feature ForgettingCode0
Personalized Federated Learning with Local Attention—0
Resolution-Invariant Image Classification based on Fourier Neural OperatorsCode0
CNNs with Multi-Level Attention for Domain Generalization—0
Parents and Children: Distinguishing Multimodal DeepFakes from Natural ImagesCode1
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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