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 82268250 of 10420 papers

TitleStatusHype
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural NetworksCode0
Are Straight-Through gradients and Soft-Thresholding all you need for Sparse Training?Code0
PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and HumansCode0
Recoverable Privacy-Preserving Image Classification through Noise-like Adversarial ExamplesCode0
Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative PretrainingCode0
Reconciliation of Statistical and Spatial Sparsity For Robust Image and Image-Set ClassificationCode0
Recombinator Networks: Learning Coarse-to-Fine Feature AggregationCode0
Reciprocal Supervised Learning Improves Neural Machine TranslationCode0
Recipe recognition with large multimodal food datasetCode0
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture SearchCode0
Recent Advances in Deep Learning for Object DetectionCode0
[Re] A Reproduction of Ensemble Distribution DistillationCode0
Real-valued continued fraction of straight linesCode0
Real-Time Weather Image Classification with SVMCode0
Facing the Void: Overcoming Missing Data in Multi-View ImageryCode0
ADVISE: ADaptive Feature Relevance and VISual Explanations for Convolutional Neural NetworksCode0
Enhancing Self-Supervised Learning for Remote Sensing with Elevation Data: A Case Study with Scarce And High Level Semantic LabelsCode0
A Baseline for Few-Shot Image ClassificationCode0
Real-Time Edge Classification: Optimal Offloading under Token Bucket ConstraintsCode0
Real-Time Damage Detection in Fiber Lifting Ropes Using Lightweight Convolutional Neural NetworksCode0
Real-Time Correlation Tracking via Joint Model Compression and TransferCode0
Facilitated machine learning for image-based fruit quality assessmentCode0
Face Spoofing Detection using Deep LearningCode0
Extreme Memorization via Scale of InitializationCode0
Rapid-INR: Storage Efficient CPU-free DNN Training Using Implicit Neural RepresentationCode0
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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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified