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 3151–3200 of 10419 papers

TitleStatusHype
Discovering Discriminative Cell Attributes for HEp-2 Specimen Image Classification—0
Generating Hard Examples for Pixel-wise Classification—0
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks—0
DLCFT: Deep Linear Continual Fine-Tuning for General Incremental Learning—0
Bombus Species Image Classification—0
DISCO: Distributed Inference with Sparse Communications—0
DM-CT: Consistency Training with Data and Model Perturbation—0
DMSANet: Dual Multi Scale Attention Network—0
Block-wise Scrambled Image Recognition Using Adaptation Network—0
Do Better ImageNet Models Transfer Better?—0
Disaggregated Deep Learning via In-Physics Computing at Radio Frequency—0
Do Convnets Learn Correspondence?—0
Do Convolutional Neural Networks Learn Class Hierarchy?—0
Document AI: Benchmarks, Models and Applications—0
Block-term Tensor Neural Networks—0
Document image classification, with a specific view on applications of patent images—0
An Efficient Technique for Image Captioning using Deep Neural Network—0
Detached Error Feedback for Distributed SGD with Random Sparsification—0
Increasing Depth Leads to U-Shaped Test Risk in Over-parameterized Convolutional Networks—0
Exploring Cross-Domain Pretrained Model for Hyperspectral Image Classification—0
DiSa: Directional Saliency-Aware Prompt Learning for Generalizable Vision-Language Models—0
Does Data Augmentation Benefit from Split BatchNorms—0
An Evoked Potential-Guided Deep Learning Brain Representation For Visual Classification—0
Does deep learning model calibration improve performance in class-imbalanced medical image classification?—0
Exploiting LMM-based knowledge for image classification tasks—0
Blockout: Dynamic Model Selection for Hierarchical Deep Networks—0
Exploiting Local Features from Deep Networks for Image Retrieval—0
Does Haze Removal Help CNN-based Image Classification?—0
Dirichlet-based Histogram Feature Transform for Image Classification—0
Blockchain Enabled Trustless API Marketplace—0
ADFQ-ViT: Activation-Distribution-Friendly Post-Training Quantization for Vision Transformers—0
Does Robustness on ImageNet Transfer to Downstream Tasks?—0
Blink: Fast and Generic Collectives for Distributed ML—0
Does Visual Pretraining Help End-to-End Reasoning?—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
Exploiting Category Names for Few-Shot Classification with Vision-Language Models—0
Domain2Vec: Deep Domain Generalization—0
Domain Adaptation and Image Classification via Deep Conditional Adaptation Network—0
An Efficient and Small Convolutional Neural Network for Pest Recognition -- ExquisiteNet—0
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models—0
Domain Adaptive Monocular Depth Estimation With Semantic Information—0
Explicitly Modeled Attention Maps for Image Classification—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
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
Direct Image Classification from Fourier Ptychographic Microscopy Measurements without Reconstruction—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