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 12511275 of 10420 papers

TitleStatusHype
CLCC: Contrastive Learning for Color ConstancyCode1
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label NoiseCode1
Automated Learning Rate Scheduler for Large-batch TrainingCode1
CLCNet: Rethinking of Ensemble Modeling with Classification Confidence NetworkCode1
Object Segmentation Without Labels with Large-Scale Generative ModelsCode1
CLIP4IDC: CLIP for Image Difference CaptioningCode1
CLIP-guided Federated Learning on Heterogeneous and Long-Tailed DataCode1
Aggregated Residual Transformations for Deep Neural NetworksCode1
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object NavigationCode1
Automatically designing CNN architectures using genetic algorithm for image classificationCode1
CLIP meets DINO for Tuning Zero-Shot Classifier using Unlabeled Image CollectionsCode1
Bilinear MLPs enable weight-based mechanistic interpretabilityCode1
Editable Neural NetworksCode1
Efficient Classification of Very Large Images with Tiny ObjectsCode1
FocusNet: Classifying Better by Focusing on Confusing ClassesCode1
CNN Filter DB: An Empirical Investigation of Trained Convolutional FiltersCode1
Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image ClassificationCode1
A survey on attention mechanisms for medical applications: are we moving towards better algorithms?Code1
All you need is a good initCode1
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image ClassificationCode1
Bias Loss for Mobile Neural NetworksCode1
BiasPruner: Debiased Continual Learning for Medical Image ClassificationCode1
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODECode1
ClusterFormer: Clustering As A Universal Visual LearnerCode1
Bi-directional Weakly Supervised Knowledge Distillation for Whole Slide Image ClassificationCode1
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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