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 39013925 of 10420 papers

TitleStatusHype
Image classification and retrieval with random depthwise signed convolutional neural networksCode0
Facilitated machine learning for image-based fruit quality assessmentCode0
Impact of Fully Connected Layers on Performance of Convolutional Neural Networks for Image ClassificationCode0
Improving Confident-Classifiers For Out-of-distribution DetectionCode0
I-CEE: Tailoring Explanations of Image Classification Models to User ExpertiseCode0
AlgebraNetsCode0
iCLIP: Bridging Image Classification and Contrastive Language-Image Pre-Training for Visual RecognitionCode0
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter OptimizationCode0
Cartoon Face Recognition: A Benchmark DatasetCode0
I Bet You Did Not Mean That: Testing Semantic Importance via BettingCode0
DartsReNet: Exploring new RNN cells in ReNet architecturesCode0
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual LearningCode0
IDEA: Image Description Enhanced CLIP-AdapterCode0
HyperZZW Operator Connects Slow-Fast Networks for Full Context InteractionCode0
Hyperspectral Image Classification With Contrastive Graph Convolutional NetworkCode0
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture SearchCode0
SLICE: Stabilized LIME for Consistent Explanations for Image ClassificationCode0
Tuned Compositional Feature Replays for Efficient Stream LearningCode0
Robust and accelerated single-spike spiking neural network training with applicability to challenging temporal tasksCode0
Hysteresis Activation Function for Efficient InferenceCode0
Smooth Grad-CAM++: An Enhanced Inference Level Visualization Technique for Deep Convolutional Neural Network ModelsCode0
Are Straight-Through gradients and Soft-Thresholding all you need for Sparse Training?Code0
Hyperspectral Image Classification via Sparse Representation With Incremental DictionariesCode0
DAP: Detection-Aware Pre-training with Weak SupervisionCode0
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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