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 88768900 of 10420 papers

TitleStatusHype
PAGANDA: An Adaptive Task-Independent Automatic Data AugmentationCode0
HyperZZW Operator Connects Slow-Fast Networks for Full Context InteractionCode0
Tuned Compositional Feature Replays for Efficient Stream LearningCode0
ColorNet -- Estimating Colorfulness in Natural ImagesCode0
Hysteresis Activation Function for Efficient InferenceCode0
Attention Gated Networks: Learning to Leverage Salient Regions in Medical ImagesCode0
Attention Branch Network: Learning of Attention Mechanism for Visual ExplanationCode0
Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step DefencesCode0
PALM: Pushing Adaptive Learning Rate Mechanisms for Continual Test-Time AdaptationCode0
Domain-independent Dominance of Adaptive MethodsCode0
ColorMAE: Exploring data-independent masking strategies in Masked AutoEncodersCode0
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual LearningCode0
I Bet You Did Not Mean That: Testing Semantic Importance via BettingCode0
Domain Generalization with Vital Phase AugmentationCode0
Adaptive Neuron-wise Discriminant Criterion and Adaptive Center Loss at Hidden Layer for Deep Convolutional Neural NetworkCode0
Color Channel Perturbation Attacks for Fooling Convolutional Neural Networks and A Defense Against Such AttacksCode0
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
Cartoon Face Recognition: A Benchmark DatasetCode0
GANchors: Realistic Image Perturbation Distributions for Anchors Using Generative ModelsCode0
Adaptive Meta-Learning for Identification of Rover-Terrain DynamicsCode0
I-CEE: Tailoring Explanations of Image Classification Models to User ExpertiseCode0
iCLIP: Bridging Image Classification and Contrastive Language-Image Pre-Training for Visual RecognitionCode0
Parallel Grid Pooling for Data AugmentationCode0
Collaboratively Weighting Deep and Classic Representation via L2 Regularization for Image ClassificationCode0
Domain Generalization by Solving Jigsaw PuzzlesCode0
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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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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