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 501525 of 10419 papers

TitleStatusHype
Targeted Visualization of the Backbone of Encoder LLMsCode1
DeepGleason: a System for Automated Gleason Grading of Prostate Cancer using Deep Neural NetworksCode1
iDAT: inverse Distillation Adapter-TuningCode1
VLM-CPL: Consensus Pseudo Labels from Vision-Language Models for Human Annotation-Free Pathological Image ClassificationCode1
Just Shift It: Test-Time Prototype Shifting for Zero-Shot Generalization with Vision-Language ModelsCode1
Eye-gaze Guided Multi-modal Alignment for Medical Representation LearningCode1
Forward Learning of Graph Neural NetworksCode1
RadCLIP: Enhancing Radiologic Image Analysis through Contrastive Language-Image Pre-trainingCode1
InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised LearningCode1
Multi-criteria Token Fusion with One-step-ahead Attention for Efficient Vision TransformersCode1
Transformers Get Stable: An End-to-End Signal Propagation Theory for Language ModelsCode1
The First to Know: How Token Distributions Reveal Hidden Knowledge in Large Vision-Language Models?Code1
Can We Talk Models Into Seeing the World Differently?Code1
DAM: Dynamic Adapter Merging for Continual Video QA LearningCode1
Multiscale Low-Frequency Memory Network for Improved Feature Extraction in Convolutional Neural NetworksCode1
Fine-grained Prompt Tuning: A Parameter and Memory Efficient Transfer Learning Method for High-resolution Medical Image ClassificationCode1
Frequency Attention for Knowledge DistillationCode1
Defending Against Unforeseen Failure Modes with Latent Adversarial TrainingCode1
A&B BNN: Add&Bit-Operation-Only Hardware-Friendly Binary Neural NetworkCode1
Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image ClassificationCode1
Generalizable Whole Slide Image Classification with Fine-Grained Visual-Semantic InteractionCode1
SDF2Net: Shallow to Deep Feature Fusion Network for PolSAR Image ClassificationCode1
MV-Swin-T: Mammogram Classification with Multi-view Swin TransformerCode1
Perceiving Longer Sequences With Bi-Directional Cross-Attention TransformersCode1
Weakly Supervised Object Detection in Chest X-Rays with Differentiable ROI Proposal Networks and Soft ROI PoolingCode1
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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