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 9801–9850 of 10420 papers

TitleStatusHype
Tube Convolutional Neural Network (T-CNN) for Action Detection in VideosCode0
Bundle Optimization for Multi-aspect Embedding—0
Multi-Scale Dense Networks for Resource Efficient Image ClassificationCode1
Active Convolution: Learning the Shape of Convolution for Image ClassificationCode0
Scaling the Scattering Transform: Deep Hybrid NetworksCode0
Deceiving Google's Cloud Video Intelligence API Built for Summarizing Videos—0
Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image ClassificationCode1
Cross-View Image Matching for Geo-localization in Urban EnvironmentsCode0
Knowledge Transfer for Melanoma Screening with Deep LearningCode0
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes—0
Knowledge distillation using unlabeled mismatched images—0
Second-order Convolutional Neural Networks—0
Curriculum DropoutCode0
PatternNet: Visual Pattern Mining with Deep Neural Network—0
From visual words to a visual grammar: using language modelling for image classification—0
Random Forests and VGG-NET: An Algorithm for the ISIC 2017 Skin Lesion Classification Challenge—0
Transfer Learning for Melanoma Detection: Participation in ISIC 2017 Skin Lesion Classification Challenge—0
Convolutional Low-Resolution Fine-Grained Classification—0
Fully Convolutional Neural Networks to Detect Clinical Dermoscopic Features—0
Automatic Skin Lesion Analysis using Large-scale Dermoscopy Images and Deep Residual Networks—0
Evaluating Deep Convolutional Neural Networks for Material Classification—0
A Compact DNN: Approaching GoogLeNet-Level Accuracy of Classification and Domain Adaptation—0
Deep Learning applied to NLPCode0
Learning to Remember Rare EventsCode0
Image Classification of Melanoma, Nevus and Seborrheic Keratosis by Deep Neural Network EnsembleCode0
Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksCode1
Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute DetectionCode0
Multi-Level and Multi-Scale Feature Aggregation Using Pre-trained Convolutional Neural Networks for Music Auto-taggingCode0
Deep Collaborative Learning for Visual Recognition—0
Adversarial Examples for Semantic Image Segmentation—0
Large-Scale Evolution of Image ClassifiersCode0
Learning What Data to Learn—0
ShaResNet: reducing residual network parameter number by sharing weightsCode0
Auto-clustering Output Layer: Automatic Learning of Latent Annotations in Neural Networks—0
Learning Deep NBNN Representations for Robust Place Categorization—0
Mimicking Ensemble Learning with Deep Branched Networks—0
Online Representation Learning with Single and Multi-layer Hebbian Networks for Image Classification—0
Learning Spatial Regularization with Image-level Supervisions for Multi-label Image ClassificationCode0
A Survey on Deep Learning in Medical Image Analysis—0
EMNIST: an extension of MNIST to handwritten lettersCode0
A Novel Weight-Shared Multi-Stage CNN for Scale Robustness—0
Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n^2)-type of Risk Bounds—0
Search Intelligence: Deep Learning For Dominant Category Prediction—0
ImageNet MPEG-7 Visual Descriptors - Technical Report—0
Fully Convolutional Architectures for Multi-Class Segmentation in Chest RadiographsCode0
Theoretical Foundations of Forward Feature Selection Methods based on Mutual Information—0
CP-decomposition with Tensor Power Method for Convolutional Neural Networks CompressionCode0
Training Group Orthogonal Neural Networks with Privileged Information—0
Dirty Pixels: Towards End-to-End Image Processing and PerceptionCode0
Residual and Plain Convolutional Neural Networks for 3D Brain MRI ClassificationCode0
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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