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 94019425 of 10420 papers

TitleStatusHype
Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimationCode0
I-SplitEE: Image classification in Split Computing DNNs with Early ExitsCode0
Plot2API: Recommending Graphic API from Plot via Semantic Parsing Guided Neural NetworkCode0
Defense against Adversarial Attacks Using High-Level Representation Guided DenoiserCode0
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification ModelsCode0
Is user feedback always informative? Retrieval Latent Defending for Semi-Supervised Domain Adaptation without Source DataCode0
ISyNet: Convolutional Neural Networks design for AI acceleratorCode0
Multitask Deep Learning with Spectral Knowledge for Hyperspectral Image ClassificationCode0
Application of Quantum Pre-Processing Filter for Binary Image Classification with Small SamplesCode0
[Re] A Reproduction of Ensemble Distribution DistillationCode0
Application of a Convolutional Neural Network for image classification to the analysis of collisions in High Energy PhysicsCode0
A geometry-inspired decision-based attackCode0
Defending Against Physically Realizable Attacks on Image ClassificationCode0
An Iteratively Optimized Patch Label Inference Network for Automatic Pavement Distress DetectionCode0
AP-Perf: Incorporating Generic Performance Metrics in Differentiable LearningCode0
A Particle Swarm Optimization-based Flexible Convolutional Auto-Encoder for Image ClassificationCode0
Deep Visual City Recognition VisualizationCode0
Budgeted Training: Rethinking Deep Neural Network Training Under Resource ConstraintsCode0
Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute DetectionCode0
A Genetic Programming Approach to Designing Convolutional Neural Network ArchitecturesCode0
Sequentially Aggregated Convolutional NetworksCode0
Rethinking Normalization and Elimination Singularity in Neural NetworksCode0
BRIDLE: Generalized Self-supervised Learning with QuantizationCode0
A Parameterized Generative Adversarial Network Using Cyclic Projection for Explainable Medical Image ClassificationCode0
AntidoteRT: Run-time Detection and Correction of Poison Attacks on Neural NetworksCode0
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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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified