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

Showing 78767900 of 10420 papers

TitleStatusHype
Disentanglement based Active LearningCode0
Deep Poisoning: Towards Robust Image Data Sharing against Visual Disclosure0
Meta-Learning Initializations for Image SegmentationCode0
TopoAct: Visually Exploring the Shape of Activations in Deep LearningCode0
Recurrent Highway Networks with Grouped Auxiliary MemoryCode0
Towards Partial Supervision for Generic Object Counting in Natural ScenesCode0
Row-Sparse Discriminative Deep Dictionary Learning for Hyperspectral Image Classification0
Discriminative Robust Deep Dictionary Learning for Hyperspectral Image Classification0
Label Consistent Transform Learning for Hyperspectral Image Classification0
Parting with Illusions about Deep Active Learning0
Wide-Area Land Cover Mapping with Sentinel-1 Imagery using Deep Learning Semantic Segmentation Models0
Image Classification with Deep Learning in the Presence of Noisy Labels: A SurveyCode1
Associative Alignment for Few-shot Image ClassificationCode0
Scalable Fine-grained Generated Image Classification Based on Deep Metric Learning0
Feature Losses for Adversarial Robustness0
Arithmetic addition of two integers by deep image classification networks: experiments to quantify their autonomous reasoning abilityCode0
Appending Adversarial Frames for Universal Video Attack0
SpineNet: Learning Scale-Permuted Backbone for Recognition and LocalizationCode0
Deep Adaptive Wavelet NetworkCode0
Naive Gabor Networks for Hyperspectral Image Classification0
Meta-Learning without MemorizationCode0
Selective Synthetic Augmentation with Quality Assurance0
Learning Disentangled Representations via Mutual Information EstimationCode0
Principal Component Properties of Adversarial Samples0
Dynamic Convolution: Attention over Convolution KernelsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified