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 5601–5625 of 10420 papers

TitleStatusHype
2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach—0
Better Teacher Better Student: Dynamic Prior Knowledge for Knowledge DistillationCode0
Specifying and Testing k-Safety Properties for Machine-Learning ModelsCode0
Learning Task-Independent Game State Representations from Unlabeled Images—0
Learning-Based Data Storage [Vision] (Technical Report)—0
Learning the Space of Deep ModelsCode0
Training Neural Networks using SAT solvers—0
Saccade Mechanisms for Image Classification, Object Detection and Tracking—0
OOD Augmentation May Be at Odds with Open-Set Recognition—0
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint—0
Learning to generate imaginary tasks for improving generalization in meta-learning—0
Uncovering bias in the PlantVillage datasetCode0
Solving the Spike Feature Information Vanishing Problem in Spiking Deep Q Network with Potential Based Normalization—0
Improving Evaluation of Debiasing in Image Classification—0
Gradient Obfuscation Gives a False Sense of Security in Federated Learning—0
IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach—0
Pancreatic Cancer ROSE Image Classification Based on Multiple Instance Learning with Shuffle Instances—0
8-bit Numerical Formats for Deep Neural Networks—0
Is More Data All You Need? A Causal Exploration—0
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization GuaranteesCode0
Search Space Adaptation for Differentiable Neural Architecture Search in Image Classification—0
A Control Theoretic Framework for Adaptive Gradient Optimizers in Machine Learning—0
Delving into the Openness of CLIPCode0
Effects of Auxiliary Knowledge on Continual Learning—0
Supernet Training for Federated Image Classification under System HeterogeneityCode0
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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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified