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 6976–7000 of 10420 papers

TitleStatusHype
Knowledge Distillation in Generations: More Tolerant Teachers Educate Better Students—0
Knowledge Distillation for Object Detection via Rank Mimicking and Prediction-guided Feature Imitation—0
Deep Poisoning: Towards Robust Image Data Sharing against Visual Disclosure—0
Bayesian Convolutional Neural Networks for Limited Data Hyperspectral Remote Sensing Image Classification—0
AMUN: Adversarial Machine UNlearning—0
Knowledge Distillation for Incremental Learning in Semantic Segmentation—0
One-bit Supervision for Image Classification: Problem, Solution, and Beyond—0
Knowledge Concentration: Learning 100K Object Classifiers in a Single CNN—0
One-class Steel Detector Using Patch GAN Discriminator for Visualising Anomalous Feature Map—0
One-D-Piece: Image Tokenizer Meets Quality-Controllable Compression—0
On effects of Knowledge Distillation on Transfer Learning—0
Knowledge-Aware Prompt Tuning for Generalizable Vision-Language Models—0
Knowledge accumulating: The general pattern of learning—0
Deep Octonion Networks—0
Adaptive Noise-Tolerant Network for Image Segmentation—0
Knee or ROC—0
DeepObfuscator: Obfuscating Intermediate Representations with Privacy-Preserving Adversarial Learning on Smartphones—0
K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning—0
KeystoneML: Optimizing Pipelines for Large-Scale Advanced Analytics—0
Deep Nonparametric Convexified Filtering for Computational Photography, Image Synthesis and Adversarial Defense—0
Bayesian Adaptation for Covariate Shift—0
Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis—0
Kernel Task-Driven Dictionary Learning for Hyperspectral Image Classification—0
DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework—0
Kernel Reconstruction ICA for Sparse Representation—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