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 9351–9375 of 10420 papers

TitleStatusHype
IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural NetworksCode0
HydraNets: Specialized Dynamic Architectures for Efficient Inference—0
Accurate and Efficient Similarity Search for Large Scale Face Recognition—0
Generating Image Captions in Arabic using Root-Word Based Recurrent Neural Networks and Deep Neural Networks—0
OLÉ: Orthogonal Low-Rank Embedding - A Plug and Play Geometric Loss for Deep LearningCode0
Rotation Equivariance and Invariance in Convolutional Neural NetworksCode0
Adversarial Attacks on Face Detectors using Neural Net based Constrained Optimization—0
Multiaccuracy: Black-Box Post-Processing for Fairness in ClassificationCode0
Multi-function Convolutional Neural Networks for Improving Image Classification Performance—0
Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels—0
Deep Learning under Privileged Information Using Heteroscedastic DropoutCode0
Object-Level Representation Learning for Few-Shot Image Classification—0
Fast Dynamic Routing Based on Weighted Kernel Density EstimationCode0
CapsNet comparative performance evaluation for image classification—0
Adversarial Examples in Remote Sensing—0
Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks—0
Calibrating Deep Convolutional Gaussian ProcessesCode0
Accelerating CNN inference on FPGAs: A Survey—0
Transductive Label Augmentation for Improved Deep Network Learning—0
Transfer Learning for Illustration ClassificationCode0
Do Better ImageNet Models Transfer Better?—0
Non-convex non-local flows for saliency detection—0
Hyperspectral image classification via a random patches networkCode0
"Why Should I Trust Interactive Learners?" Explaining Interactive Queries of Classifiers to Users—0
Unsupervised Domain Adaptation using Regularized Hyper-graph Matching—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
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