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 6151–6175 of 10420 papers

TitleStatusHype
Learning to Learn Image Classifiers with Visual Analogy—0
MaskConnect: Connectivity Learning by Gradient Descent—0
Be Your Own Best Competitor! Multi-Branched Adversarial Knowledge Transfer—0
An Analysis of the Expressiveness of Deep Neural Network Architectures Based on Their Lipschitz Constants—0
Learning to Learn: How to Continuously Teach Humans and Machines—0
Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing—0
Detecting Overfitting via Adversarial Examples—0
Learning to generate imaginary tasks for improving generalization in meta-learning—0
Detecting Novelties with Empty Classes—0
Learning to Generate Images with Perceptual Similarity Metrics—0
Learning to Generate Image Embeddings with User-level Differential Privacy—0
Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis—0
Beyond the Visible: Multispectral Vision-Language Learning for Earth Observation—0
An Analysis of Pre-Training on Object Detection—0
AdaScale SGD: A Scale-Invariant Algorithm for Distributed Training—0
A Class of Short-term Recurrence Anderson Mixing Methods and Their Applications—0
2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach—0
Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks—0
Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps—0
Matching Feature Sets for Few-Shot Image Classification—0
Learning to Detect Semantic Boundaries with Image-level Class Labels—0
Beyond the Attention: Distinguish the Discriminative and Confusable Features For Fine-grained Image Classification—0
Learning to Detect Malicious Clients for Robust Federated Learning—0
Matrix Is All You Need—0
Learning to Detect Blue-white Structures in Dermoscopy Images with Weak Supervision—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