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

Showing 46014650 of 10420 papers

TitleStatusHype
AmsterTime: A Visual Place Recognition Benchmark Dataset for Severe Domain ShiftCode0
SIT: A Bionic and Non-Linear Neuron for Spiking Neural Network0
Classification of NEQR Processed Classical Images using Quantum Neural Networks (QNN)0
4Weed Dataset: Annotated Imagery Weeds Dataset0
VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer DatasetCode1
Treatment Learning Causal Transformer for Noisy Image Classification0
CNN Filter DB: An Empirical Investigation of Trained Convolutional FiltersCode1
CHEX: CHannel EXploration for CNN Model CompressionCode1
Edge Detection and Deep Learning Based SETI Signal Classification Method0
Nested Collaborative Learning for Long-Tailed Visual RecognitionCode1
Parameter-efficient Model Adaptation for Vision TransformersCode1
A Fast and Efficient Conditional Learning for Tunable Trade-Off between Accuracy and Robustness0
A Novel Approach for detecting Normal, COVID-19 and Pneumonia patient using only binary classifications from chest CT-ScansCode1
Neurosymbolic hybrid approach to driver collision warning0
Learning to Prompt for Open-Vocabulary Object Detection with Vision-Language ModelCode1
WSEBP: A Novel Width-depth Synchronous Extension-based Basis Pursuit Algorithm for Multi-Layer Convolutional Sparse CodingCode0
Knowledge Mining with Scene Text for Fine-Grained RecognitionCode1
How to Robustify Black-Box ML Models? A Zeroth-Order Optimization PerspectiveCode1
On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks0
Image quality assessment for machine learning tasks using meta-reinforcement learning0
On the Viability of Monocular Depth Pre-training for Semantic SegmentationCode0
Uncertainty-aware Contrastive Distillation for Incremental Semantic SegmentationCode1
Give Me Your Attention: Dot-Product Attention Considered Harmful for Adversarial Patch Robustness0
Contrastive learning of Class-agnostic Activation Map for Weakly Supervised Object Localization and Semantic SegmentationCode2
A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network CalibrationCode1
Moving Window Regression: A Novel Approach to Ordinal RegressionCode1
The Fixed Sub-Center: A Better Way to Capture Data Complexity0
Transformers Meet Visual Learning Understanding: A Comprehensive Review0
Locally Asynchronous Stochastic Gradient Descent for Decentralised Deep Learning0
A Two-Stage Federated Transfer Learning Framework in Medical Images Classification on Limited Data: A COVID-19 Case Study0
A DNN Optimizer that Improves over AdaBelief by Suppression of the Adaptive Stepsize RangeCode0
NPC: Neuron Path Coverage via Characterizing Decision Logic of Deep Neural Networks0
Multidimensional Belief Quantification for Label-Efficient Meta-LearningCode0
Efficient Fully Distributed Federated Learning with Adaptive Local Links0
Semisupervised Cross-scale Graph Prototypical Network for Hyperspectral Image ClassificationCode1
Visual Prompt TuningCode3
U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture SearchCode0
FedDC: Federated Learning with Non-IID Data via Local Drift Decoupling and CorrectionCode1
DTFD-MIL: Double-Tier Feature Distillation Multiple Instance Learning for Histopathology Whole Slide Image ClassificationCode1
Improving Generalization in Federated Learning by Seeking Flat MinimaCode1
PaCa-ViT: Learning Patch-to-Cluster Attention in Vision TransformersCode1
Feature Distribution Matching for Federated Domain GeneralizationCode0
Generative Modeling Helps Weak Supervision (and Vice Versa)Code0
Semi-Targeted Model Poisoning Attack on Federated Learning via Backward Error AnalysisCode0
Robust Classification using Contractive Hamiltonian Neural ODEsCode0
Focal Modulation NetworksCode2
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward0
Training Quantised Neural Networks with STE Variants: the Additive Noise Annealing Algorithm0
Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices0
ViM: Out-Of-Distribution with Virtual-logit MatchingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified