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 5651–5675 of 10420 papers

TitleStatusHype
Learning Augmentation Network via Influence Functions—0
Learning-Based Data Storage [Vision] (Technical Report)—0
Learning Binary Codes and Binary Weights for Efficient Classification—0
Critical Hyper-Parameters: No Random, No Cry—0
Attention-based Natural Language Person Retrieval—0
Handwritten digit and letter recognition using hybrid dwt-dct with knn and svm classifier—0
Learning Class-to-Image Distance with Object Matchings—0
Learning CNN filters from user-drawn image markers for coconut-tree image classification—0
CRISPnet: Color Rendition ISP Net—0
HAMIL: Hierarchical Aggregation-Based Multi-Instance Learning for Microscopy Image Classification—0
Hallucinating Saliency Maps for Fine-Grained Image Classification for Limited Data Domains—0
Learning Connectivity of Neural Networks from a Topological Perspective—0
Attention-based Image Upsampling—0
Learning Consistent Deep Generative Models from Sparse Data via Prediction Constraints—0
Learning Contextual Dependencies with Convolutional Hierarchical Recurrent Neural Networks—0
Learning Continually from Low-shot Data Stream—0
A Hybrid Method for Training Convolutional Neural Networks—0
Learning Cross-domain Generalizable Features by Representation Disentanglement—0
Linear Spatial Pyramid Matching Using Non-convex and non-negative Sparse Coding for Image Classification—0
Learning cross space mapping via DNN using large scale click-through logs—0
Half-CNN: A General Framework for Whole-Image Regression—0
Cribriform pattern detection in prostate histopathological images using deep learning models—0
HAct: Out-of-Distribution Detection with Neural Net Activation Histograms—0
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification—0
CRAM: Clued Recurrent Attention Model—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