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 7726–7750 of 10420 papers

TitleStatusHype
Content and Context Features for Scene Image Representation—0
A Simplified 2D-3D CNN Architecture for Hyperspectral Image Classification Based on Spatial–Spectral Fusion—0
Deep Sequential Feature Learning in Clinical Image Classification of Infectious Keratitis—0
Learning Multi-Modal Nonlinear Embeddings: Performance Bounds and an Algorithm—0
Image Classification in the Dark using Quanta Image Sensors—0
Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations—0
Probabilistic Structural Latent Representation for Unsupervised EmbeddingCode0
Rotation Consistent Margin Loss for Efficient Low-Bit Face Recognition—0
Predicting Lymph Node Metastasis Using Histopathological Images Based on Multiple Instance Learning With Deep Graph Convolution—0
Polishing Decision-Based Adversarial Noise With a Customized Sampling—0
Erasing Integrated Learning: A Simple Yet Effective Approach for Weakly Supervised Object Localization—0
Efficient Neural Vision Systems Based on Convolutional Image Acquisition—0
ADINet: Attribute Driven Incremental Network for Retinal Image Classification—0
Distilling Image Dehazing With Heterogeneous Task ImitationCode0
BFBox: Searching Face-Appropriate Backbone and Feature Pyramid Network for Face Detector—0
Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration—0
Learning Augmentation Network via Influence Functions—0
Latent Domain Learning with Dynamic Residual Adapters—0
BadNL: Backdoor Attacks against NLP Models with Semantic-preserving Improvements—0
DeepEMD: Few-Shot Image Classification With Differentiable Earth Mover's Distance and Structured Classifiers—0
Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data—0
Deep Degradation Prior for Low-Quality Image Classification—0
SmoothMix: A Simple Yet Effective Data Augmentation to Train Robust Classifiers—0
Rethinking Computer-Aided Tuberculosis Diagnosis—0
Hyperspectral Image Classification of Convolutional Neural Network Combined with Valuable Samples—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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