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 72767300 of 10420 papers

TitleStatusHype
Ramanujan Bipartite Graph Products for Efficient Block Sparse Neural Networks0
When Do Neural Networks Outperform Kernel Methods?Code0
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction0
Hyperparameter Ensembles for Robustness and Uncertainty QuantificationCode0
Calibration of Neural Networks using SplinesCode1
Post-hoc Calibration of Neural Networks by g-Layers0
Don’t Wait, Just Weight: Improving Unsupervised Representations by Learning Goal-Driven Instance Weights0
Auxiliary Learning by Implicit Differentiation0
RP2K: A Large-Scale Retail Product Dataset for Fine-Grained Image Classification0
Effective Version Space Reduction for Convolutional Neural Networks0
DO-Conv: Depthwise Over-parameterized Convolutional LayerCode1
On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AIDCode1
The color out of space: learning self-supervised representations for Earth Observation imageryCode1
Self-Knowledge Distillation with Progressive Refinement of TargetsCode1
A Universal Representation Transformer Layer for Few-Shot Image ClassificationCode1
FNA++: Fast Network Adaptation via Parameter Remapping and Architecture SearchCode1
MaxVA: Fast Adaptation of Step Sizes by Maximizing Observed Variance of GradientsCode0
Gradient-EM Bayesian Meta-learning0
A Bayesian Evaluation Framework for Subjectively Annotated Visual Recognition TasksCode0
Adversarial Transfer of Pose Estimation Regression0
Unsupervised Image Classification for Deep Representation LearningCode0
Deep Polynomial Neural NetworksCode1
Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual RecognitionCode1
Paying more attention to snapshots of Iterative Pruning: Improving Model Compression via Ensemble DistillationCode1
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning0
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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