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 4576–4600 of 10420 papers

TitleStatusHype
Grouped Pointwise Convolutions Significantly Reduces Parameters in EfficientNetCode0
Growing a Brain with Sparsity-Inducing Generation for Continual LearningCode0
Grounding Stylistic Domain Generalization with Quantitative Domain Shift Measures and Synthetic Scene ImagesCode0
Bridging Lottery Ticket and Grokking: Understanding Grokking from Inner Structure of NetworksCode0
A Bayesian Approach to OOD Robustness in Image ClassificationCode0
Group Downsampling with Equivariant Anti-aliasingCode0
Hardware Resilience Properties of Text-Guided Image ClassifiersCode0
IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural NetworksCode0
An Intelligent Remote Sensing Image Quality Inspection SystemCode0
LIP: Local Importance-based PoolingCode0
Graph-Weighted Contrastive Learning for Semi-Supervised Hyperspectral Image ClassificationCode0
MGIC: Multigrid-in-Channels Neural Network ArchitecturesCode0
Few-Shot Histopathology Image Classification: Evaluating State-of-the-Art Methods and Unveiling Performance Insights—0
Computation and Communication Efficient Lightweighting Vertical Federated Learning for Smart Building IoT—0
Few-shot crack image classification using clip based on bayesian optimization—0
Few-Shot Classification & Segmentation Using Large Language Models Agent—0
Computational Integration of Human Vision and Natural Language through Bitext Alignment—0
Few-shot Algorithm Assurance—0
Few-shot Action Recognition with Implicit Temporal Alignment and Pair Similarity Optimization—0
Few-Shot Action Recognition with Compromised Metric via Optimal Transport—0
Compressive spectral image classification using 3D coded convolutional neural network—0
AFINets: Attentive Feature Integration Networks for Image Classification—0
Compressively Sensed Image Recognition—0
FETCH: A Memory-Efficient Replay Approach for Continual Learning in Image Classification—0
Ferrograph image classification—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