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 5551–5575 of 10420 papers

TitleStatusHype
Attention-free Spikformer: Mixing Spike Sequences with Simple Linear Transforms—0
Learning with Recursive Perceptual Representations—0
Ladder Networks for Semi-Supervised Hyperspectral Image Classification—0
HASeparator: Hyperplane-Assisted Softmax—0
LANCE: Efficient Low-Precision Quantized Winograd Convolution for Neural Networks Based on Graphics Processing Units—0
Land Cover Classification from Multi-temporal, Multi-spectral Remotely Sensed Imagery using Patch-Based Recurrent Neural Networks—0
HASA: Hybrid Architecture Search with Aggregation Strategy for Echinococcosis Classification and Ovary Segmentation in Ultrasound Images—0
Landscape of Neural Architecture Search across sensors: how much do they differ ?—0
Cross Domain Ensemble Distillation for Domain Generalization—0
Bayesian Test-Time Adaptation for Vision-Language Models—0
Language-aware Domain Generalization Network for Cross-Scene Hyperspectral Image Classification—0
Harvesting Mid-level Visual Concepts from Large-Scale Internet Images—0
Cross-domain Deep Feature Combination for Bird Species Classification with Audio-visual Data—0
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention—0
Language-Informed Hyperspectral Image Synthesis for Imbalanced-Small Sample Classification via Semi-Supervised Conditional Diffusion Model—0
LeDNet: Localization-enabled Deep Neural Network for Multi-Label Radiography Image Classification—0
Attention Enables Zero Approximation Error—0
Harnessing The Power of Attention For Patch-Based Biomedical Image Classification—0
Learning with Neighbor Consistency for Noisy Labels—0
Harnessing Increased Client Participation with Cohort-Parallel Federated Learning—0
LARE: Latent Augmentation using Regional Embedding with Vision-Language Model—0
Large e-retailer image dataset for visual search and product classification—0
Cross-Domain Collaborative Learning via Cluster Canonical Correlation Analysis and Random Walker for Hyperspectral Image Classification—0
Large Language Models Implicitly Learn to See and Hear Just By Reading—0
Accelerating CNN inference on FPGAs: A Survey—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