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 676–700 of 10419 papers

TitleStatusHype
ANDHRA Bandersnatch: Training Neural Networks to Predict Parallel RealitiesCode0
MVFormer: Diversifying Feature Normalization and Token Mixing for Efficient Vision Transformers—0
Fall Leaf Adversarial Attack on Traffic Sign Classification—0
Mixture of Experts in Image Classification: What's the Sweet Spot?—0
Optimized Tradeoffs for Private Prediction with Majority Ensembling—0
Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data—0
Pruning Deep Convolutional Neural Network Using Conditional Mutual Information—0
Spectral-Spatial Transformer with Active Transfer Learning for Hyperspectral Image ClassificationCode1
Vision Mamba Distillation for Low-resolution Fine-grained Image ClassificationCode1
KANs for Computer Vision: An Experimental Study—0
Task Singular Vectors: Reducing Task Interference in Model MergingCode2
BadScan: An Architectural Backdoor Attack on Visual State Space Models—0
CoA: Chain-of-Action for Generative Semantic LabelsCode0
TinyViM: Frequency Decoupling for Tiny Hybrid Vision MambaCode2
An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models—0
SpikeAtConv: An Integrated Spiking-Convolutional Attention Architecture for Energy-Efficient Neuromorphic Vision Processing—0
Debiasing Classifiers by Amplifying Bias with Latent Diffusion and Large Language Models—0
Creating Scalable AGI: the Open General Intelligence Framework—0
MUNBa: Machine Unlearning via Nash BargainingCode0
Twin Trigger Generative Networks for Backdoor Attacks against Object Detection—0
PaRCE: Probabilistic and Reconstruction-based Competency Estimation for CNN-based Image ClassificationCode0
FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image ClassificationCode1
MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMsCode3
EfficientViM: Efficient Vision Mamba with Hidden State Mixer based State Space DualityCode2
CODE-CL: Conceptor-Based Gradient Projection for Deep Continual LearningCode1
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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