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

Showing 39263950 of 10420 papers

TitleStatusHype
FakeFormer: Efficient Vulnerability-Driven Transformers for Generalisable Deepfake DetectionCode0
Image-Caption Encoding for Improving Zero-Shot GeneralizationCode0
IDEA: Image Description Enhanced CLIP-AdapterCode0
Network DeconvolutionCode0
Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image ClassificationCode0
Robust and accelerated single-spike spiking neural network training with applicability to challenging temporal tasksCode0
iCLIP: Bridging Image Classification and Contrastive Language-Image Pre-Training for Visual RecognitionCode0
Identification of Stone Deterioration Patterns with Large Multimodal ModelsCode0
Cartoon Face Recognition: A Benchmark DatasetCode0
DAP: Detection-Aware Pre-training with Weak SupervisionCode0
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
I-CEE: Tailoring Explanations of Image Classification Models to User ExpertiseCode0
Identifying Adversarially Attackable and Robust SamplesCode0
Image classification and retrieval with random depthwise signed convolutional neural networksCode0
Augmenting Prototype Network with TransMix for Few-shot Hyperspectral Image ClassificationCode0
Tuned Compositional Feature Replays for Efficient Stream LearningCode0
DANet: Divergent Activation for Weakly Supervised Object LocalizationCode0
Hysteresis Activation Function for Efficient InferenceCode0
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual LearningCode0
Hyperspectral Image Classification With Contrastive Graph Convolutional NetworkCode0
Augmenting Data with Mixup for Sentence Classification: An Empirical StudyCode0
HyperZZW Operator Connects Slow-Fast Networks for Full Context InteractionCode0
I Bet You Did Not Mean That: Testing Semantic Importance via BettingCode0
Compact Bilinear PoolingCode0
Hyperspectral image classification via a random patches networkCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified