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 26262650 of 10420 papers

TitleStatusHype
Keep your distance: learning dispersed embeddings on S_m0
Optimizing Knowledge Distillation in Transformers: Enabling Multi-Head Attention without Alignment Barriers0
MoENAS: Mixture-of-Expert based Neural Architecture Search for jointly Accurate, Fair, and Robust Edge Deep Neural Networks0
From Image to Video: An Empirical Study of Diffusion Representations0
Beyond Batch Learning: Global Awareness Enhanced Domain Adaptation0
Amnesia as a Catalyst for Enhancing Black Box Pixel Attacks in Image Classification and Object DetectionCode0
Krum Federated Chain (KFC): Using blockchain to defend against adversarial attacks in Federated LearningCode0
Provably Near-Optimal Federated Ensemble Distillation with Negligible OverheadCode0
Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks0
Efficient Global Neural Architecture SearchCode0
Interpretable Failure Detection with Human-Level Concepts0
Training-free Neural Architecture Search through Variance of Knowledge of Deep Network WeightsCode0
AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers0
Expanding Training Data for Endoscopic Phenotyping of Eosinophilic Esophagitis0
Augmented Conditioning Is Enough For Effective Training Image Generation0
Hybrid Deep Learning Framework for Classification of Kidney CT Images: Diagnosis of Stones, Cysts, and Tumors0
Clinically-Inspired Hierarchical Multi-Label Classification of Chest X-rays with a Penalty-Based Loss FunctionCode0
Long-tailed Medical Diagnosis with Relation-aware Representation Learning and Iterative Classifier CalibrationCode0
DILLEMA: Diffusion and Large Language Models for Multi-Modal AugmentationCode0
Disentangling CLIP for Multi-Object Perception0
BRIDLE: Generalized Self-supervised Learning with QuantizationCode0
The Skin Game: Revolutionizing Standards for AI Dermatology Model ComparisonCode0
DCT-Mamba3D: Spectral Decorrelation and Spatial-Spectral Feature Extraction for Hyperspectral Image Classification0
CoRPA: Adversarial Image Generation for Chest X-rays Using Concept Vector Perturbations and Generative Models0
Generative Data Mining with Longtail-Guided Diffusion0
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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