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
Sample selection with noise rate estimation in noise learning of medical image analysis0
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models0
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation0
GROOD: Gradient-Aware Out-of-Distribution Detection0
Federated Learning via Input-Output Collaborative DistillationCode1
TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron ProvenanceCode1
Joint Sensing and Task-Oriented Communications with Image and Wireless Data Modalities for Dynamic Spectrum Access0
Q-SENN: Quantized Self-Explaining Neural NetworksCode1
Universal Noise Annotation: Unveiling the Impact of Noisy annotation on Object DetectionCode1
Open-Set: ID Card Presentation Attack Detection using Neural Transfer Style0
Unlocking Pre-trained Image Backbones for Semantic Image Synthesis0
Enhancing Neural Training via a Correlated Dynamics Model0
Testing the Segment Anything Model on radiology data0
Cached Transformers: Improving Transformers with Differentiable Memory CacheCode1
Integration and Performance Analysis of Artificial Intelligence and Computer Vision Based on Deep Learning Algorithms0
Near-Optimal Resilient Aggregation Rules for Distributed Learning Using 1-Center and 1-Mean Clustering with OutliersCode0
Unsupervised Segmentation of Colonoscopy Images0
Unveiling Spaces: Architecturally meaningful semantic descriptions from images of interior spaces0
Convolutional Channel-wise Competitive Learning for the Forward-Forward AlgorithmCode1
Optimizing Neural Networks with Gradient Lexicase SelectionCode0
Adversarial AutoMixupCode1
I-CEE: Tailoring Explanations of Image Classification Models to User ExpertiseCode0
Delving Deeper Into Astromorphic Transformers0
Learning Interpretable Queries for Explainable Image Classification with Information Pursuit0
Semantic-Aware Autoregressive Image Modeling for Visual Representation LearningCode1
Show:102550
← PrevPage 82 of 417Next →

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