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 1501–1550 of 10419 papers

TitleStatusHype
Bridging the Gap: Multi-Level Cross-Modality Joint Alignment for Visible-Infrared Person Re-IdentificationCode1
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor SegmentationCode1
AutoAssist: A Framework to Accelerate Training of Deep Neural NetworksCode1
CLIP the Gap: A Single Domain Generalization Approach for Object DetectionCode1
Knowledge Distillation Using Hierarchical Self-Supervision Augmented DistributionCode1
DCT-CryptoNets: Scaling Private Inference in the Frequency DomainCode1
Black-box Few-shot Knowledge DistillationCode1
Denoised Smoothing: A Provable Defense for Pretrained ClassifiersCode1
Decision Stream: Cultivating Deep Decision TreesCode1
Deep Fast Vision: Accelerated Deep Transfer Learning Vision Prototyping and BeyondCode1
Addressing Failure Prediction by Learning Model ConfidenceCode1
Blacklight: Scalable Defense for Neural Networks against Query-Based Black-Box AttacksCode1
CLIP4IDC: CLIP for Image Difference CaptioningCode1
Deep Subdomain Adaptation Network for Image ClassificationCode1
Understanding the Role of the Projector in Knowledge DistillationCode1
CLIP-guided Federated Learning on Heterogeneous and Long-Tailed DataCode1
Language Models as Black-Box Optimizers for Vision-Language ModelsCode1
Dilated convolution with learnable spacingsCode1
DATA: Domain-Aware and Task-Aware Self-supervised LearningCode1
Data-Efficient Deep Learning Method for Image Classification Using Data Augmentation, Focal Cosine Loss, and EnsembleCode1
"BNN - BN = ?": Training Binary Neural Networks without Batch NormalizationCode1
Grafting Transformer on Automatically Designed Convolutional Neural Network for Hyperspectral Image ClassificationCode1
Data Augmentation with norm-VAE for Unsupervised Domain AdaptationCode1
Latency-aware Spatial-wise Dynamic NetworksCode1
Lawin Transformer: Improving Semantic Segmentation Transformer with Multi-Scale Representations via Large Window AttentionCode1
Boosting Convolutional Neural Networks with Middle Spectrum Grouped ConvolutionCode1
A General Regret Bound of Preconditioned Gradient Method for DNN TrainingCode1
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object NavigationCode1
Learnable Lookup Table for Neural Network QuantizationCode1
Polynomial, trigonometric, and tropical activationsCode1
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP)Code1
Learn From Others and Be Yourself in Heterogeneous Federated LearningCode1
An Empirical Investigation of the Role of Pre-training in Lifelong LearningCode1
Learning Binary Semantic Embedding for Histology Image Classification and RetrievalCode1
Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNetsCode1
Clusterability as an Alternative to Anchor Points When Learning with Noisy LabelsCode1
Learning Filter Basis for Convolutional Neural Network CompressionCode1
Learning From Noisy Labels By Regularized Estimation Of Annotator ConfusionCode1
A deep active learning system for species identification and counting in camera trap imagesCode1
Learning Invariances in Neural NetworksCode1
Learning Multimodal Data Augmentation in Feature SpaceCode1
Boosting Multi-Label Image Classification with Complementary Parallel Self-DistillationCode1
Data Feedback Loops: Model-driven Amplification of Dataset BiasesCode1
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution EnvironmentsCode1
Learning Representations For Images With Hierarchical LabelsCode1
Boosting the Adversarial Transferability of Surrogate Models with Dark KnowledgeCode1
Danish Fungi 2020 -- Not Just Another Image Recognition DatasetCode1
DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data AugmentationCode1
Learning Support and Trivial Prototypes for Interpretable Image ClassificationCode1
DARTS: Differentiable Architecture SearchCode1
Show:102550
← PrevPage 31 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