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 14511475 of 10420 papers

TitleStatusHype
Learning From Noisy Labels By Regularized Estimation Of Annotator ConfusionCode1
Maximum Likelihood with Bias-Corrected Calibration is Hard-To-Beat at Label Shift AdaptationCode1
Generative Latent Implicit Conditional Optimization when Learning from Small SampleCode1
Learning Invariances in Neural NetworksCode1
Explaining in Style: Training a GAN to explain a classifier in StyleSpaceCode1
Learning Representational Invariances for Data-Efficient Action RecognitionCode1
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot LearningCode1
Deep Factorized Metric LearningCode1
AdaScale SGD: A User-Friendly Algorithm for Distributed TrainingCode1
Deep Fast Vision: A Python Library for Accelerated Deep Transfer Learning Vision PrototypingCode1
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural NetworksCode1
Deep Fast Vision: Accelerated Deep Transfer Learning Vision Prototyping and BeyondCode1
Revisiting the Importance of Amplifying Bias for DebiasingCode1
Bias Loss for Mobile Neural NetworksCode1
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over ModulesCode1
BiasPruner: Debiased Continual Learning for Medical Image ClassificationCode1
Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image ClassificationCode1
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image ClassificationCode1
Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image ClassificationCode1
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use caseCode1
A General Regret Bound of Preconditioned Gradient Method for DNN TrainingCode1
Deep Hyperspectral Unmixing using Transformer NetworkCode1
Object Segmentation Without Labels with Large-Scale Generative ModelsCode1
Explaining and Harnessing Adversarial ExamplesCode1
Explaining Latent Representations with a Corpus of ExamplesCode1
Show:102550
← PrevPage 59 of 417Next →

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