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 5176–5200 of 10420 papers

TitleStatusHype
Equivariance with Learned Canonicalization Functions—0
Dual Complementary Dynamic Convolution for Image Recognition—0
Token Transformer: Can class token help window-based transformer build better long-range interactions?—0
Depth and Representation in Vision ModelsCode0
REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of studyCode0
MGiaD: Multigrid in all dimensions. Efficiency and robustness by coarsening in resolution and channel dimensions—0
On the Robustness of deep learning-based MRI Reconstruction to image transformations—0
Framework Construction of an Adversarial Federated Transfer Learning Classifier—0
Understanding the Role of Mixup in Knowledge Distillation: An Empirical StudyCode0
Learning advisor networks for noisy image classificationCode0
Detecting Shortcuts in Medical Images -- A Case Study in Chest X-raysCode0
Automatic Error Detection in Integrated Circuits Image Segmentation: A Data-driven Approach—0
Temporal superimposed crossover module for effective continuous sign language—0
FIXED: Frustratingly Easy Domain Generalization with Mixup—0
SAFA: Sample-Adaptive Feature Augmentation for Long-Tailed Image Classification—0
KGTN-ens: Few-Shot Image Classification with Knowledge Graph EnsemblesCode0
A Robust and Low Complexity Deep Learning Model for Remote Sensing Image Classification—0
Rate-Distortion Optimized Post-Training Quantization for Learned Image Compression—0
Multi-Objective Evolutionary for Object Detection Mobile Architectures Search—0
WaveNets: Wavelet Channel Attention NetworksCode0
Exploring Explainability Methods for Graph Neural Networks—0
Evaluating a Synthetic Image Dataset Generated with Stable Diffusion—0
Deep neural network based on F-neurons and its learningCode0
Hardware/Software co-design with ADC-Less In-memory Computing Hardware for Spiking Neural Networks—0
MuMIC -- Multimodal Embedding for Multi-label Image Classification with Tempered Sigmoid—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