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 6101–6150 of 10420 papers

TitleStatusHype
Pyramid Adversarial Training Improves ViT PerformanceCode0
MC-SSL0.0: Towards Multi-Concept Self-Supervised Learning—0
I-CNet: Leveraging Involution and Convolution for Image Classification—0
Human Imperceptible Attacks and Applications to Improve Fairness—0
Anomaly-Aware Semantic Segmentation by Leveraging Synthetic-Unknown Data—0
Building extraction with vision transformer—0
OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images—0
On the Effectiveness of Neural Ensembles for Image Classification with Small Datasets—0
Weakly-supervised Generative Adversarial Networks for medical image classification—0
EffCNet: An Efficient CondenseNet for Image Classification on NXP BlueBox—0
Detecting Adversaries, yet Faltering to Noise? Leveraging Conditional Variational AutoEncoders for Adversary Detection in the Presence of Noisy Images—0
Sparse Subspace Clustering Friendly Deep Dictionary Learning for Hyperspectral Image Classification—0
Reinforcement Explanation Learning—0
FedDropoutAvg: Generalizable federated learning for histopathology image classification—0
Natural & Adversarial Bokeh Rendering via Circle-of-Confusion Predictive Network—0
ExPLoit: Extracting Private Labels in Split Learning—0
Global Interaction Modelling in Vision Transformer via Super Tokens—0
Transferability Estimation using Bhattacharyya Class Separability—0
Application of deep learning to camera trap data for ecologists in planning / engineering -- Can captivity imagery train a model which generalises to the wild?—0
An Image Patch is a Wave: Phase-Aware Vision MLPCode0
Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates—0
Improved Fine-Tuning by Better Leveraging Pre-Training Data—0
Spatial-context-aware deep neural network for multi-class image classification—0
MorphMLP: An Efficient MLP-Like Backbone for Spatial-Temporal Representation LearningCode0
CoDiM: Learning with Noisy Labels via Contrastive Semi-Supervised Learning—0
Multi-label Iterated Learning for Image Classification with Label AmbiguityCode0
Inducing Functions through Reinforcement Learning without Task Specification—0
Using mixup as regularization and tuning hyper-parameters for ResNetsCode0
Metamorphic Adversarial Detection Pipeline for Face Recognition Systems—0
Adversarial Examples on Segmentation Models Can be Easy to Transfer—0
Broad Adversarial Training with Data Augmentation in the Output Space—0
Linearised Laplace Inference in Networks with Normalisation Layers and the Neural g-Prior—0
Learning Consistent Deep Generative Models from Sparsely Labeled Data—0
Nanorobot queue: Cooperative treatment of cancer based on team member communication and image processing—0
MiNet: A Convolutional Neural Network for Identifying and Categorising Minerals—0
Deep Learning Based Automated COVID-19 Classification from Computed Tomography ImagesCode0
Revisiting Adversarial Robustness of Classifiers With a Reject Option—0
DBIA: Data-free Backdoor Injection Attack against Transformer NetworksCode0
XnODR and XnIDR: Two Accurate and Fast Fully Connected Layers For Convolutional Neural NetworksCode0
Are Vision Transformers Robust to Patch Perturbations?—0
Medical Knowledge-Guided Deep Learning for Imbalanced Medical Image Classification—0
Discrete Representations Strengthen Vision Transformer RobustnessCode0
FBNetV5: Neural Architecture Search for Multiple Tasks in One Run—0
Combined Scaling for Zero-shot Transfer Learning—0
A 3D 2D convolutional Neural Network Model for Hyperspectral Image Classification—0
Rethinking Query, Key, and Value Embedding in Vision Transformer under Tiny Model Constraints—0
Understanding Training-Data Leakage from Gradients in Neural Networks for Image ClassificationCode0
COVID-19 Detection on Chest X-Ray Images: A comparison of CNN architectures and ensemblesCode0
Fairness Testing of Deep Image Classification with Adequacy Metrics—0
Two-step adversarial debiasing with partial learning -- medical image case-studies—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