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 10761100 of 10419 papers

TitleStatusHype
Oral squamous cell detection using deep learning0
Image Class Translation Distance: A Novel Interpretable Feature for Image Classification0
Tell Codec What Worth Compressing: Semantically Disentangled Image Coding for Machine with LMMs0
LEVIS: Large Exact Verifiable Input Spaces for Neural Networks0
Efficient Image-to-Image Diffusion Classifier for Adversarial RobustnessCode1
DPA: Dual Prototypes Alignment for Unsupervised Adaptation of Vision-Language ModelsCode0
MM-UNet: A Mixed MLP Architecture for Improved Ophthalmic Image Segmentation0
5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition TasksCode3
Predictive uncertainty estimation in deep learning for lung carcinoma classification in digital pathology under real dataset shifts0
Beyond Uniform Query Distribution: Key-Driven Grouped Query AttentionCode0
Activation Space Selectable Kolmogorov-Arnold Networks0
Moving Healthcare AI-Support Systems for Visually Detectable Diseases onto Constrained Devices0
SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-trainingCode2
Towards flexible perception with visual memoryCode1
Category-Prompt Refined Feature Learning for Long-Tailed Multi-Label Image ClassificationCode1
HAIR: Hypernetworks-based All-in-One Image RestorationCode2
Leveraging Perceptual Scores for Dataset Pruning in Computer Vision Tasks0
Orchid2024: A cultivar-level dataset and methodology for fine-grained classification of Chinese Cymbidium OrchidsCode0
Concept Graph Embedding Models for Enhanced Accuracy and InterpretabilityCode0
Towards Cross-Domain Single Blood Cell Image Classification via Large-Scale LoRA-based Segment Anything ModelCode1
Do Vision-Language Foundational models show Robust Visual Perception?Code0
Efficient Search for Customized Activation Functions with Gradient DescentCode0
Coherence Awareness in Diffractive Neural NetworksCode0
Global-to-Local Support Spectrums for Language Model Explainability0
Targeted Deep Learning System Boundary TestingCode0
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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