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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 7301–7325 of 10420 papers

TitleStatusHype
Polish Corpus of Annotated Descriptions of Images—0
From images in the wild to video-informed image classification—0
Patchnet: Interpretable Neural Networks for Image Classification—0
Contextual Recurrent Convolutional Model for Robust Visual Learning—0
From Dictionary of Visual Words to Subspaces: Locality-Constrained Affine Subspace Coding—0
Patch-wise Features for Blur Image Classification—0
From Categories to Subcategories: Large-Scale Image Classification With Partial Class Label Refinement—0
Contextual Local Explanation for Black Box Classifiers—0
AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference—0
PathM3: A Multimodal Multi-Task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning—0
From Categories to Classifiers: Name-Only Continual Learning by Exploring the Web—0
From BOP to BOSS and Beyond: Time Series Classification with Dictionary Based Classifiers—0
Exploiting auto-encoders and segmentation methods for middle-level explanations of image classification systems—0
PAT: Pseudo-Adversarial Training For Detecting Adversarial Videos—0
From augmented microscopy to the topological transformer: a new approach in cell image analysis for Alzheimer's research—0
Adversarial Examples for Edge Detection: They Exist, and They Transfer—0
Policy Smoothing for Provably Robust Reinforcement Learning—0
Pavement Fatigue Crack Detection and Severity Classification Based on Convolutional Neural Network—0
Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning—0
Polishing Decision-Based Adversarial Noise With a Customized Sampling—0
POMONAG: Pareto-Optimal Many-Objective Neural Architecture Generator—0
From Artificial Intelligence to Brain Intelligence: The basis learning and memory algorithm for brain-like intelligence—0
PoET-BiN: Power Efficient Tiny Binary Neurons—0
Temporal Output Discrepancy for Loss Estimation-based Active Learning—0
POGD: Gradient Descent with New Stochastic Rules—0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10RevCol-HTop 1 Accuracy90—Unverified