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 12011225 of 10419 papers

TitleStatusHype
ConvMLP: Hierarchical Convolutional MLPs for VisionCode1
Augmenting Convolutional networks with attention-based aggregationCode1
Babel-ImageNet: Massively Multilingual Evaluation of Vision-and-Language RepresentationsCode1
AGI-Elo: How Far Are We From Mastering A Task?Code1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
Diagnose Like a Pathologist: Transformer-Enabled Hierarchical Attention-Guided Multiple Instance Learning for Whole Slide Image ClassificationCode1
Convolutional Channel-wise Competitive Learning for the Forward-Forward AlgorithmCode1
Masking meets Supervision: A Strong Learning AllianceCode1
Differentiable Model Compression via Pseudo Quantization NoiseCode1
Differentiable Model Scaling using Differentiable TopkCode1
Controllable Orthogonalization in Training DNNsCode1
AugMix: A Simple Data Processing Method to Improve Robustness and UncertaintyCode1
Abstracting Deep Neural Networks into Concept Graphs for Concept Level InterpretabilityCode1
Diffusion Mechanism in Residual Neural Network: Theory and ApplicationsCode1
Convolutional Sequence to Sequence LearningCode1
BAGAN: Data Augmentation with Balancing GANCode1
A Unified Algebraic Perspective on Lipschitz Neural NetworksCode1
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasksCode1
Adapting Grad-CAM for Embedding NetworksCode1
Direct Differentiable Augmentation SearchCode1
Direct Parameterization of Lipschitz-Bounded Deep NetworksCode1
Dirichlet-based Uncertainty Calibration for Active Domain AdaptationCode1
Discretization-Aware Architecture SearchCode1
Discrimination-aware Network Pruning for Deep Model CompressionCode1
A Survey on Transferability of Adversarial Examples across Deep Neural NetworksCode1
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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