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 9101–9125 of 10420 papers

TitleStatusHype
Domain transfer through deep activation matching—0
Geolocation Estimation of Photos using a Hierarchical Model and Scene ClassificationCode0
Correcting the Triplet Selection Bias for Triplet LossCode0
Open Set Learning with Counterfactual Images—0
Evaluating Capability of Deep Neural Networks for Image Classification via Information Plane—0
DetNet: Design Backbone for Object Detection—0
Dynamic Conditional Networks for Few-Shot Learning—0
Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification—0
Transductive Semi-Supervised Deep Learning using Min-Max Features—0
Scalable Exemplar-based Subspace Clustering on Class-Imbalanced Data—0
Semi-Supervised Deep Learning with MemoryCode0
SphereNet: Learning Spherical Representations for Detection and Classification in Omnidirectional Images—0
Data Dropout: Optimizing Training Data for Convolutional Neural Networks—0
Seeing Colors: Learning Semantic Text Encoding for Classification—0
Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation—0
Fixed-Point Convolutional Neural Network for Real-Time Video Processing in FPGACode0
Cross-Domain Collaborative Learning via Cluster Canonical Correlation Analysis and Random Walker for Hyperspectral Image Classification—0
Top-down Attention Recurrent VLAD Encoding for Action Recognition in Videos—0
Searching Toward Pareto-Optimal Device-Aware Neural Architectures—0
Tensor Alignment Based Domain Adaptation for Hyperspectral Image Classification—0
Motorcycle Classification in Urban Scenarios using Convolutional Neural Networks for Feature Extraction—0
How do Convolutional Neural Networks Learn Design?—0
An Improvement of Data Classification Using Random Multimodel Deep Learning (RMDL)Code0
Maximal Jacobian-based Saliency Map Attack—0
Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' BlocksCode1
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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