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 2451–2500 of 10419 papers

TitleStatusHype
COLORA: Efficient Fine-Tuning for Convolutional Models with a Study Case on Optical Coherence Tomography Image Classification—0
Co-localization with Category-Consistent Features and Geodesic Distance Propagation—0
A Continual Learning Framework for Adaptive Defect Classification and Inspection—0
Collective Learning—0
Collage Inference: Using Coded Redundancy for Low Variance Distributed Image Classification—0
A Randomized Zeroth-Order Hierarchical Framework for Heterogeneous Federated Learning—0
AAVAE: Augmentation-Augmented Variational Autoencoders—0
Collage Inference: Achieving low tail latency during distributed image classification using coded redundancy models—0
Collaborative Image Understanding—0
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense—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
Domain transfer through deep activation matching—0
Don’t Wait, Just Weight: Improving Unsupervised Representations by Learning Goal-Driven Instance Weights—0
DTG-Net: Differentiated Teachers Guided Self-Supervised Video Action Recognition—0
Collaboration of Experts: Achieving 80% Top-1 Accuracy on ImageNet with 100M FLOPs—0
Adversarial Robustness on Image Classification with k-means—0
Do humans and machines have the same eyes? Human-machine perceptual differences on image classification—0
CoLa-DCE -- Concept-guided Latent Diffusion Counterfactual Explanations—0
Adversarial Robustness in Deep Learning: Attacks on Fragile Neurons—0
CognitiveNet: Enriching Foundation Models with Emotions and Awareness—0
CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning—0
A Push-Pull Layer Improves Robustness of Convolutional Neural Networks—0
A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black-Scholes partial differential equations—0
Dolphin: Closed-loop Open-ended Auto-research through Thinking, Practice, and Feedback—0
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks—0
A Progressive Framework of Vision-language Knowledge Distillation and Alignment for Multilingual Scene—0
COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation—0
Adversarial Robustness Assessment of NeuroEvolution Approaches—0
Adversarial Robustness Across Representation Spaces—0
A probabilistic patch based image representation using Conditional Random Field model for image classification—0
A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images—0
Coarse to Fine: Multi-label Image Classification with Global/Local Attention—0
CoAPT: Context Attribute words for Prompt Tuning—0
Forget the Learning Rate, Decay Loss—0
Domain2Vec: Deep Domain Generalization—0
A Privacy Preserving Method with a Random Orthogonal Matrix for ConvMixer Models—0
A concatenating framework of shortcut convolutional neural networks—0
CO2: Consistent Contrast for Unsupervised Visual Representation Learning—0
A privacy-preserving method using secret key for convolutional neural network-based speech classification—0
Does Saliency-Based Training bring Robustness for Deep Neural Networks in Image Classification?—0
CNN with large memory layers—0
A Priori Generalizability Estimate for a CNN—0
Adversarial Perturbations Against Deep Neural Networks for Malware Classification—0
CNNs with Multi-Level Attention for Domain Generalization—0
CNN: Single-label to Multi-label—0
A priori compression of convolutional neural networks for wave simulators—0
PreMix: Addressing Label Scarcity in Whole Slide Image Classification with Pre-trained Multiple Instance Learning Aggregators—0
Does Visual Pretraining Help End-to-End Reasoning?—0
CNNs Avoid Curse of Dimensionality by Learning on Patches—0
Show:102550
← PrevPage 50 of 209Next →
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