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

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Showing 5651–5700 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
Locally-Supervised Deep Hybrid Model for Scene Recognition—0
Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples—0
Critic Loss for Image Classification—0
Learning Class-to-Image Distance with Object Matchings—0
Learning CNN filters from user-drawn image markers for coconut-tree image classification—0
HAO: Hardware-aware neural Architecture Optimization for Efficient Inference—0
DefMamba: Deformable Visual State Space Model—0
FEATHERS: Federated Architecture and Hyperparameter Search—0
Learning Connectivity of Neural Networks from a Topological Perspective—0
Critical Hyper-Parameters: No Random, No Cry—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
Attention-based Natural Language Person Retrieval—0
Learning Cross-domain Generalizable Features by Representation Disentanglement—0
Handwritten digit and letter recognition using hybrid dwt-dct with knn and svm classifier—0
Learning cross space mapping via DNN using large scale click-through logs—0
CRISPnet: Color Rendition ISP Net—0
Benchmarking the Robustness of Semantic Segmentation Models—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
Attention-based Image Upsampling—0
A Hybrid Method for Training Convolutional Neural Networks—0
Delay Differential Neural Networks—0
Learning Deep Context-Network Architectures for Image Annotation—0
Local Binary Pattern(LBP) Optimization for Feature Extraction—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
Learning degraded image classification with restoration data fidelity—0
Learning Dependency Structures for Weak Supervision Models—0
Learning Discriminative Features Via Weights-biased Softmax Loss—0
Learning Discriminative Multilevel Structured Dictionaries for Supervised Image Classification—0
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification—0
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework—0
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification—0
CRAM: Clued Recurrent Attention Model—0
Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks—0
GvT: A Graph-based Vision Transformer with Talking-Heads Utilizing Sparsity, Trained from Scratch on Small Datasets—0
A Hybrid Generative and Discriminative PointNet on Unordered Point Sets—0
Learning efficient structured dictionary for image classification—0
Guiding the retraining of convolutional neural networks against adversarial inputs—0
Creating Scalable AGI: the Open General Intelligence Framework—0
LMM-Regularized CLIP Embeddings for Image Classification—0
Learning Expressive Prompting With Residuals for Vision Transformers—0
LMSA: Low-relation Mutil-head Self-Attention Mechanism in Visual Transformer—0
Local Color Contrastive Descriptor for Image Classification—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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified