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 6201–6250 of 10420 papers

TitleStatusHype
2nd Place Solution for ICCV 2021 VIPriors Image Classification Challenge: An Attract-and-Repulse Learning Approach—0
Learning to Find Correlated Features by Maximizing Information Flow in Convolutional Neural Networks—0
Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps—0
Learning to Detect Semantic Boundaries with Image-level Class Labels—0
Beyond the Attention: Distinguish the Discriminative and Confusable Features For Fine-grained Image Classification—0
Learning to Detect Malicious Clients for Robust Federated Learning—0
Learning to Detect Blue-white Structures in Dermoscopy Images with Weak Supervision—0
MDL-NAS: A Joint Multi-Domain Learning Framework for Vision Transformer—0
Learning to Complement with Multiple Humans—0
Beyond Size and Class Balance: Alpha as a New Dataset Quality Metric for Deep Learning—0
Learning to combine foveal glimpses with a third-order Boltzmann machine—0
Learning To Collaborate in Decentralized Learning of Personalized Models—0
Learning to Classify New Foods Incrementally Via Compressed Exemplars—0
Detecting Adversaries, yet Faltering to Noise? Leveraging Conditional Variational AutoEncoders for Adversary Detection in the Presence of Noisy Images—0
Learning to be Global Optimizer—0
Learning to aggregate feature representations—0
Detecting Adversarial Perturbations with Saliency—0
Measuring the Success of Diffusion Models at Imitating Human Artists—0
Efficient Object Embedding for Spliced Image Retrieval—0
MECFormer: Multi-task Whole Slide Image Classification with Expert Consultation Network—0
Adaptive Weighting Scheme for Automatic Time-Series Data Augmentation—0
Learning to Adapt Category Consistent Meta-Feature of CLIP for Few-Shot Classification—0
Detecting Adversarial Perturbations Through Spatial Behavior in Activation Spaces—0
Learning Through Guidance: Knowledge Distillation for Endoscopic Image Classification—0
Learning The Structure of Deep Convolutional Networks—0
Beyond Linearity: Squeeze-and-Recalibrate Blocks for Few-Shot Whole Slide Image Classification—0
Detecting Adversarial Examples in Convolutional Neural Networks—0
Medical Image Segmentation using LeViT-UNet++: A Case Study on GI Tract Data—0
Learning the Connections in Direct Feedback Alignment—0
Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis—0
Beyond Inference: Performance Analysis of DNN Server Overheads for Computer Vision—0
Learning Task-Independent Game State Representations from Unlabeled Images—0
Learning task-agnostic representation via toddler-inspired learning—0
MedKAN: An Advanced Kolmogorov-Arnold Network for Medical Image Classification—0
Detecção da Psoríase Utilizando Visão Computacional: Uma Abordagem Comparativa Entre CNNs e Vision Transformers—0
Learning Subclass Representations for Visually-varied Image Classification—0
Learning Structures for Deep Neural Networks—0
Learning Structured Low-Rank Representations for Image Classification—0
Design-time Fashion Popularity Forecasting in VR Environments—0
Beyond image classification: zooplankton identification with deep vector space embeddings—0
Analyzing the Use of Influence Functions for Instance-Specific Data Filtering in Neural Machine Translation—0
Adaptive Test-Time Augmentation for Low-Power CPU—0
A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning—0
Membership Inference Attacks Against Text-to-image Generation Models—0
Membership Inference Attacks fueled by Few-Short Learning to detect privacy leakage tackling data integrity—0
Learning Structured Inference Neural Networks with Label Relations—0
Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence—0
Design of Supervision-Scalable Learning Systems: Methodology and Performance Benchmarking—0
Memory- and Communication-Aware Model Compression for Distributed Deep Learning Inference on IoT—0
Beyond Image Classification: A Video Benchmark and Dual-Branch Hybrid Discrimination Framework for Compositional Zero-Shot Learning—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified