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 21012125 of 10420 papers

TitleStatusHype
Convolutional Sequence to Sequence LearningCode1
Consistency-based Active Learning for Object DetectionCode1
A Spectral-Spatial-Dependent Global Learning Framework for Insufficient and Imbalanced Hyperspectral Image ClassificationCode1
Convolution-enhanced Evolving Attention NetworksCode1
OccamNet: A Fast Neural Model for Symbolic Regression at ScaleCode1
Interpreting and Analysing CLIP's Zero-Shot Image Classification via Mutual KnowledgeCode1
CorGAN: Correlation-Capturing Convolutional Generative Adversarial Networks for Generating Synthetic Healthcare RecordsCode1
Invariant Information Clustering for Unsupervised Image Classification and SegmentationCode1
InceptionMamba: An Efficient Hybrid Network with Large Band Convolution and Bottleneck MambaCode1
Investigating and Explaining the Frequency Bias in Image ClassificationCode1
Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional NetworksCode1
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy LabelsCode1
Iterative Reorganization with Weak Spatial Constraints: Solving Arbitrary Jigsaw Puzzles for Unsupervised Representation LearningCode1
It's All in the Head: Representation Knowledge Distillation through Classifier SharingCode1
Counterfactual Visual ExplanationsCode1
Co-Tuning for Transfer LearningCode1
Counterfactual Generative NetworksCode1
Just Shift It: Test-Time Prototype Shifting for Zero-Shot Generalization with Vision-Language ModelsCode1
Container: Context Aggregation NetworkCode1
A fuzzy distance-based ensemble of deep models for cervical cancer detectionCode1
Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?Code1
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision TransformersCode1
Learning Hierarchical Image Segmentation For Recognition and By RecognitionCode1
COVID-CXNet: Detecting COVID-19 in Frontal Chest X-ray Images using Deep LearningCode1
Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?Code1
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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