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 1551–1575 of 10419 papers

TitleStatusHype
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution EnvironmentsCode1
Danish Fungi 2020 -- Not Just Another Image Recognition DatasetCode1
Learning to Unlearn: Instance-wise Unlearning for Pre-trained ClassifiersCode1
Bootstrap your own latent: A new approach to self-supervised LearningCode1
Layer-adaptive sparsity for the Magnitude-based PruningCode1
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture SearchCode1
BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split ComputingCode1
DARTS: Differentiable Architecture SearchCode1
Robust Models Are More Interpretable Because Attributions Look NormalCode1
Learning Visual Representations for Transfer Learning by Suppressing TextureCode1
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label MiscorrectionCode1
Learning with Noisy labels via Self-supervised Adversarial Noisy MaskingCode1
Bounding Boxes Are All We Need: Street View Image Classification via Context Encoding of Detected BuildingsCode1
An Ensemble of Simple Convolutional Neural Network Models for MNIST Digit RecognitionCode1
Less is More: Lighter and Faster Deep Neural Architecture for Tomato Leaf Disease ClassificationCode1
Less is More: Pay Less Attention in Vision TransformersCode1
DATA: Domain-Aware and Task-Aware Self-supervised LearningCode1
CoCa: Contrastive Captioners are Image-Text Foundation ModelsCode1
L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient and Accurate Deep LearningCode1
DAF:re: A Challenging, Crowd-Sourced, Large-Scale, Long-Tailed Dataset For Anime Character RecognitionCode1
A Neural Dirichlet Process Mixture Model for Task-Free Continual LearningCode1
Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction UncertaintyCode1
Lightweight Neural Architecture Search for Temporal Convolutional Networks at the EdgeCode1
Linear Attention with Global Context: A Multipole Attention Mechanism for Vision and PhysicsCode1
CyCNN: A Rotation Invariant CNN using Polar Mapping and Cylindrical Convolution LayersCode1
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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