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 17761800 of 10419 papers

TitleStatusHype
Class Distance Weighted Cross-Entropy Loss for Ulcerative Colitis Severity EstimationCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
Designing Network Design SpacesCode1
A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network CalibrationCode1
PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision TransformersCode1
Pseudo-Prompt Generating in Pre-trained Vision-Language Models for Multi-Label Medical Image ClassificationCode1
PseudoSeg: Designing Pseudo Labels for Semantic SegmentationCode1
CorGAN: Correlation-Capturing Convolutional Generative Adversarial Networks for Generating Synthetic Healthcare RecordsCode1
Meta-Weight-Net: Learning an Explicit Mapping For Sample WeightingCode1
PVT v2: Improved Baselines with Pyramid Vision TransformerCode1
Pychop: Emulating Low-Precision Arithmetic in Numerical Methods and Neural NetworksCode1
Pyramid Scene Parsing NetworkCode1
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without ConvolutionsCode1
Age Estimation Using Expectation of Label Distribution LearningCode1
QPM: Discrete Optimization for Globally Interpretable Image ClassificationCode1
Deep Polynomial Neural NetworksCode1
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy LabelsCode1
DeepNoise: Signal and Noise Disentanglement based on Classifying Fluorescent Microscopy Images via Deep LearningCode1
LR-Net: A Block-based Convolutional Neural Network for Low-Resolution Image ClassificationCode1
Adversarial AutoMixupCode1
RankDNN: Learning to Rank for Few-shot LearningCode1
RapidNet: Multi-Level Dilated Convolution Based Mobile BackboneCode1
Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?Code1
Real-Fake: Effective Training Data Synthesis Through Distribution MatchingCode1
Deep Prototypical Networks with Hybrid Residual Attention for Hyperspectral Image ClassificationCode1
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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