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 901925 of 10419 papers

TitleStatusHype
Adversarial Continual LearningCode1
From ImageNet to Image Classification: Contextualizing Progress on BenchmarksCode1
A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network InferenceCode1
Designing Network Design SpacesCode1
DetCo: Unsupervised Contrastive Learning for Object DetectionCode1
A Partially Reversible U-Net for Memory-Efficient Volumetric Image SegmentationCode1
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path AggregationCode1
Depth Uncertainty in Neural NetworksCode1
Compressing Features for Learning with Noisy LabelsCode1
Compressive Visual RepresentationsCode1
Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional NetworksCode1
Concept Learners for Few-Shot LearningCode1
Adversarial Example Detection for DNN Models: A Review and Experimental ComparisonCode1
Learning Hierarchical Image Segmentation For Recognition and By RecognitionCode1
Anytime Dense Prediction with Confidence AdaptivityCode1
CondenseNet V2: Sparse Feature Reactivation for Deep NetworksCode1
Gaussian RAM: Lightweight Image Classification via Stochastic Retina-Inspired Glimpse and Reinforcement LearningCode1
GazeGNN: A Gaze-Guided Graph Neural Network for Chest X-ray ClassificationCode1
Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small DatasetsCode1
Generalized Few-Shot Video Classification with Video Retrieval and Feature GenerationCode1
Adversarial Examples in Deep Learning for Multivariate Time Series RegressionCode1
Confidence Regularized Self-TrainingCode1
A Comprehensive Survey on Graph Neural NetworksCode1
Conformer: Local Features Coupling Global Representations for Visual RecognitionCode1
A General Framework For Detecting Anomalous Inputs to DNN ClassifiersCode1
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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