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 20262050 of 10420 papers

TitleStatusHype
Towards Feature Space Adversarial AttackCode1
Towards General and Efficient Active LearningCode1
Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural NetworkCode1
Towards Interpretable Radiology Report Generation via Concept Bottlenecks using a Multi-Agentic RAGCode1
Towards Interpretable Semantic Segmentation via Gradient-weighted Class Activation MappingCode1
Towards Robust and Reproducible Active Learning Using Neural NetworksCode1
Towards Robust Classification Model by Counterfactual and Invariant Data GenerationCode1
Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional NetworksCode1
SSIVD-Net: A Novel Salient Super Image Classification & Detection Technique for Weaponized ViolenceCode1
Designing Network Design SpacesCode1
Densely Connected Convolutional NetworksCode1
Stateful ODE-Nets using Basis Function ExpansionsCode1
Compressing Features for Learning with Noisy LabelsCode1
A Second-Order Approach to Learning with Instance-Dependent Label NoiseCode1
Trainable Noise Model as an XAI evaluation method: application on Sobol for remote sensing image segmentationCode1
Training Compact CNNs for Image Classification using Dynamic-coded Filter FusionCode1
Training data-efficient image transformers & distillation through attentionCode1
Training objective drives the consistency of representational similarity across datasetsCode1
Compressive Visual RepresentationsCode1
Dense Contrastive Learning for Self-Supervised Visual Pre-TrainingCode1
Training on Thin Air: Improve Image Classification with Generated DataCode1
Dendritic Learning-incorporated Vision Transformer for Image RecognitionCode1
DenoiseRep: Denoising Model for Representation LearningCode1
Depth Uncertainty in Neural NetworksCode1
Delving into Out-of-Distribution Detection with Medical Vision-Language ModelsCode1
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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