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 35513575 of 10420 papers

TitleStatusHype
General Adversarial Defense Against Black-box Attacks via Pixel Level and Feature Level Distribution Alignments0
Using Multiple Instance Learning to Build Multimodal Representations0
Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification0
Algorithmic progress in computer vision0
An AI-Powered VVPAT Counter for Elections in IndiaCode0
Dual adaptive training of photonic neural networks0
Reminding Forgetful Organic Neuromorphic Device Networks0
Frugal Reinforcement-based Active Learning0
Expeditious Saliency-guided Mix-up through Random Gradient ThresholdingCode0
Open Vocabulary Semantic Segmentation with Patch Aligned Contrastive LearningCode1
Co-training 2^L Submodels for Visual Recognition0
A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies OthersCode1
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG0
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization0
Models Developed for Spiking Neural Networks0
Development Of A Fire Detection System On Satellite Images0
Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization0
IncepFormer: Efficient Inception Transformer with Pyramid Pooling for Semantic SegmentationCode1
Causal Inference via Style Transfer for Out-of-distribution GeneralisationCode1
Mixer: DNN Watermarking using Image Mixup0
Straggler-Resilient Differentially-Private Decentralized Learning0
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances0
PØDA: Prompt-driven Zero-shot Domain AdaptationCode1
I2MVFormer: Large Language Model Generated Multi-View Document Supervision for Zero-Shot Image Classification0
Location-Aware Self-Supervised Transformers for Semantic Segmentation0
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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