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 3176–3200 of 10420 papers

TitleStatusHype
Exploiting LMM-based knowledge for image classification tasks—0
Blockout: Dynamic Model Selection for Hierarchical Deep Networks—0
Does Haze Removal Help CNN-based Image Classification?—0
Exploiting Local Features from Deep Networks for Image Retrieval—0
Dirichlet-based Histogram Feature Transform for Image Classification—0
ADFQ-ViT: Activation-Distribution-Friendly Post-Training Quantization for Vision Transformers—0
Does Robustness on ImageNet Transfer to Downstream Tasks?—0
Blockchain Enabled Trustless API Marketplace—0
Does Visual Pretraining Help End-to-End Reasoning?—0
Blink: Fast and Generic Collectives for Distributed ML—0
Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks—0
Exploiting Kernel Compression on BNNs—0
Exploiting Nontrivial Connectivity for Automatic Speech Recognition—0
Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs—0
Domain2Vec: Deep Domain Generalization—0
Domain Adaptation and Image Classification via Deep Conditional Adaptation Network—0
Exploiting Category Names for Few-Shot Classification with Vision-Language Models—0
An Efficient and Small Convolutional Neural Network for Pest Recognition -- ExquisiteNet—0
Domain Adaptive Monocular Depth Estimation With Semantic Information—0
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models—0
Domain Adaptive Skin Lesion Classification via Conformal Ensemble of Vision Transformers—0
Domain Adaptive Transfer Learning on Visual Attention Aware Data Augmentation for Fine-grained Visual Categorization—0
Explicitly Modeled Attention Maps for Image Classification—0
Exploiting Contextual Uncertainty of Visual Data for Efficient Training of Deep Models—0
Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping—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
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