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 4901–4925 of 10420 papers

TitleStatusHype
Exploring Deep Learning Methods for Classification of SAR Images: Towards NextGen Convolutions via Transformers—0
Collaborative Image Understanding—0
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense—0
A Continual Learning Framework for Adaptive Defect Classification and Inspection—0
AAVAE: Augmentation-Augmented Variational Autoencoders—0
WaveMamba: Spatial-Spectral Wavelet Mamba for Hyperspectral Image Classification—0
Advancements in Image Classification using Convolutional Neural Network—0
Exploring Data Augmentations on Self-/Semi-/Fully- Supervised Pre-trained Models—0
Exploring Cross-Domain Pretrained Model for Hyperspectral Image Classification—0
Exploring Category-correlated Feature for Few-shot Image Classification—0
Exploring Camera Encoder Designs for Autonomous Driving Perception—0
Collaboration of Experts: Achieving 80% Top-1 Accuracy on ImageNet with 100M FLOPs—0
Exploring Adversarial Attacks against Latent Diffusion Model from the Perspective of Adversarial Transferability—0
Explore the Power of Dropout on Few-shot Learning—0
Explore the Knowledge contained in Network Weights to Obtain Sparse Neural Networks—0
CoLa-DCE -- Concept-guided Latent Diffusion Counterfactual Explanations—0
Adversarial Robustness on Image Classification with k-means—0
Explore the Effect of Data Selection on Poison Efficiency in Backdoor Attacks—0
Exploration of Noise Strategies in Semi-supervised Named Entity Classification—0
CognitiveNet: Enriching Foundation Models with Emotions and Awareness—0
Exploration of Multi-Scale Image Fusion Systems in Intelligent Medical Image Analysis—0
Detached Error Feedback for Distributed SGD with Random Sparsification—0
CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning—0
A Push-Pull Layer Improves Robustness of Convolutional Neural Networks—0
Exploiting Web Images for Dataset Construction: A Domain Robust Approach—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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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