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 5501–5525 of 10420 papers

TitleStatusHype
Towards Accurate and Robust Classification in Continuously Transitioning Industrial Sprays with Mixup—0
Moment Centralization based Gradient Descent Optimizers for Convolutional Neural NetworksCode0
Few-shot Fine-grained Image Classification via Multi-Frequency Neighborhood and Double-cross ModulationCode0
Residual and Attentional Architectures for Vector-Symbols—0
Multi-manifold Attention for Vision Transformers—0
Fully trainable Gaussian derivative convolutional layerCode0
Consistent Polyhedral Surrogates for Top-k Classification and Variants—0
Improving Deep Neural Network Random Initialization Through Neuronal RewiringCode0
Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification—0
QSAN: A Near-term Achievable Quantum Self-Attention Network—0
Sound Randomized Smoothing in Floating-Point ArithmeticsCode0
T-RECX: Tiny-Resource Efficient Convolutional neural networks with early-eXit—0
Provably Adversarially Robust Nearest Prototype ClassifiersCode0
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification—0
Universal Adaptive Data Augmentation—0
Work In Progress: Safety and Robustness Verification of Autoencoder-Based Regression Models using the NNV Tool—0
Rich Feature Distillation with Feature Affinity Module for Efficient Image Dehazing—0
Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimationCode0
Adversarial Robustness Assessment of NeuroEvolution Approaches—0
RE-Tagger: A light-weight Real-Estate Image Classifier—0
Look-ups are not (yet) all you need for deep learning inferenceCode0
Image and Model Transformation with Secret Key for Vision Transformer—0
Adversarial Style Augmentation for Domain Generalized Urban-Scene SegmentationCode0
PCCT: Progressive Class-Center Triplet Loss for Imbalanced Medical Image Classification—0
Adaptive Fine-Grained Predicates Learning for Scene Graph Generation—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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified