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 9101–9150 of 10420 papers

TitleStatusHype
Face Identification with Second-Order Pooling—0
Face Image Classification by Pooling Raw Features—0
FACET: Fairness in Computer Vision Evaluation Benchmark—0
Fact or Artifact? Revise Layer-wise Relevance Propagation on various ANN Architectures—0
Factorized Adversarial Networks for Unsupervised Domain Adaptation—0
Factors of Influence for Transfer Learning across Diverse Appearance Domains and Task Types—0
FACTUAL: A Novel Framework for Contrastive Learning Based Robust SAR Image Classification—0
Failure Prediction by Confidence Estimation of Uncertainty-Aware Dirichlet Networks—0
Fair Comparison: Quantifying Variance in Resultsfor Fine-grained Visual Categorization—0
FairDD: Fair Dataset Distillation via Synchronized Matching—0
Fair Distillation: Teaching Fairness from Biased Teachers in Medical Imaging—0
Fairness Analysis of CLIP-Based Foundation Models for X-Ray Image Classification—0
Fairness-Aware Meta-Learning via Nash Bargaining—0
Fairness Testing of Deep Image Classification with Adequacy Metrics—0
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis—0
FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification—0
FairSAM: Fair Classification on Corrupted Data Through Sharpness-Aware Minimization—0
Fair-VPT: Fair Visual Prompt Tuning for Image Classification—0
FALIP: Visual Prompt as Foveal Attention Boosts CLIP Zero-Shot Performance—0
Fall Leaf Adversarial Attack on Traffic Sign Classification—0
Fantope Regularization in Metric Learning—0
Fashion and Apparel Classification using Convolutional Neural Networks—0
Fashion CUT: Unsupervised domain adaptation for visual pattern classification in clothes using synthetic data and pseudo-labels—0
FastAdaBelief: Improving Convergence Rate for Belief-based Adaptive Optimizers by Exploiting Strong Convexity—0
Fast Adaptation with Bradley-Terry Preference Models in Text-To-Image Classification and Generation—0
Fast Adaptation with Linearized Neural Networks—0
Fast and Accurate Inference with Adaptive Ensemble Prediction for Deep Networks—0
Fast and Balanced: Efficient Label Tree Learning for Large Scale Object Recognition—0
Fast and Efficient Information Transmission with Burst Spikes in Deep Spiking Neural Networks—0
Fast, Better Training Trick --- Random Gradient—0
Real-time Chest X-Ray Distributed Decision Support for Resource-constrained Clinics—0
Fast-DENSER++: Evolving Fully-Trained Deep Artificial Neural Networks—0
Faster Adaptive Federated Learning—0
Faster and Accurate Classification for JPEG2000 Compressed Images in Networked Applications—0
Faster Inference of Integer SWIN Transformer by Removing the GELU Activation—0
Faster Training by Selecting Samples Using Embeddings—0
Fast Fine-grained Image Classification via Weakly Supervised Discriminative Localization—0
Fast Fourier Convolution Based Remote Sensor Image Object Detection for Earth Observation—0
Fast Image Classification by Boosting Fuzzy Classifiers—0
Fast Image Scanning with Deep Max-Pooling Convolutional Neural Networks—0
Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification—0
Fast Neural Architecture Construction using EnvelopeNets—0
FAST OBJECT LOCALIZATION VIA SENSITIVITY ANALYSIS—0
Fast Parametric Learning with Activation Memorization—0
Fast-ParC: Capturing Position Aware Global Feature for ConvNets and ViTs—0
FATNN: Fast and Accurate Ternary Neural Networks—0
FAT: Training Neural Networks for Reliable Inference Under Hardware Faults—0
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run—0
Feasibility of Transfer Learning: A Mathematical Framework—0
Feature Activation Map: Visual Explanation of Deep Learning Models 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
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