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 7801–7850 of 10420 papers

TitleStatusHype
Adapting Grad-CAM for Embedding NetworksCode1
Are These Birds Similar: Learning Branched Networks for Fine-grained RepresentationsCode1
Code-Bridged Classifier (CBC): A Low or Negative Overhead Defense for Making a CNN Classifier Robust Against Adversarial Attacks—0
Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised LearningCode1
Extending Class Activation Mapping Using Gaussian Receptive Field—0
Relevance Prediction from Eye-movements Using Semi-interpretable Convolutional Neural Networks—0
Towards detection and classification of microscopic foraminifera using transfer learningCode0
Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual FeaturesCode1
Multi-Complementary and Unlabeled Learning for Arbitrary Losses and Models—0
Boosting Occluded Image Classification via Subspace Decomposition Based Estimation of Deep FeaturesCode0
Semi-supervised learning method based on predefined evenly-distributed class centroids—0
Bag of Tricks for Retail Product Image ClassificationCode0
Diagnosing Colorectal Polyps in the Wild with Capsule NetworksCode1
Neural Data Server: A Large-Scale Search Engine for Transfer Learning Data—0
The Effect of Data Ordering in Image Classification—0
Transferability of Adversarial Examples to Attack Cloud-based Image Classifier ServiceCode2
Fast Neural Network Adaptation via Parameter Remapping and Architecture SearchCode0
Multimodal Semantic Transfer from Text to Image. Fine-Grained Image Classification by Distributional Semantics—0
Sparse Weight Activation TrainingCode1
Deceiving Image-to-Image Translation Networks for Autonomous Driving with Adversarial Perturbations—0
FDFtNet: Facing Off Fake Images using Fake Detection Fine-tuning NetworkCode1
The troublesome kernel -- On hallucinations, no free lunches and the accuracy-stability trade-off in inverse problemsCode0
Discrimination-aware Network Pruning for Deep Model CompressionCode1
DAF-NET: a saliency based weakly supervised method of dual attention fusion for fine-grained image classification—0
FrequentNet: A Novel Interpretable Deep Learning Model for Image ClassificationCode0
A Neural Dirichlet Process Mixture Model for Task-Free Continual LearningCode1
Improve Unsupervised Domain Adaptation with Mixup Training—0
Automated Relational Meta-learningCode1
Kernelized Support Tensor Train Machines—0
Understanding Contrastive Representation Learning through Geometry on the HypersphereCode1
Towards Accurate Post-training Network Quantization via Bit-Split and StitchingCode1
Test-Time Training for Generalization under Distribution Shifts—0
Interpolation between CNNs and ResNets—0
Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks—0
Training Deep Networks with Stochastic Gradient Normalized by Layerwise Adaptive Second Moments—0
UW-NET: AN INCEPTION-ATTENTION NETWORK FOR UNDERWATER IMAGE CLASSIFICATION—0
Differentiable Architecture Compression—0
Scalable NAS with Factorizable Architectural Parameters—0
LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingCode2
Recognizing Images with at most one Spike per Neuron—0
RC-DARTS: Resource Constrained Differentiable Architecture Search—0
Semi-Supervised Learning with Normalizing FlowsCode0
QDNN: DNN with Quantum Neural Network LayersCode0
Mixed-Precision Quantized Neural Network with Progressively Decreasing Bitwidth For Image Classification and Object Detection—0
Deep Context-Aware Kernel Networks—0
Active Learning in Video Tracking—0
NAS evaluation is frustratingly hardCode0
Statistical Loss and Analysis for Deep Learning in Hyperspectral Image ClassificationCode0
Embedding of FRPN in CNN architecture—0
Benchmarking Adversarial Robustness—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