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 98269850 of 10420 papers

TitleStatusHype
Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksCode1
Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute DetectionCode0
Multi-Level and Multi-Scale Feature Aggregation Using Pre-trained Convolutional Neural Networks for Music Auto-taggingCode0
Deep Collaborative Learning for Visual Recognition0
Adversarial Examples for Semantic Image Segmentation0
Large-Scale Evolution of Image ClassifiersCode0
Learning What Data to Learn0
ShaResNet: reducing residual network parameter number by sharing weightsCode0
Auto-clustering Output Layer: Automatic Learning of Latent Annotations in Neural Networks0
Learning Deep NBNN Representations for Robust Place Categorization0
Mimicking Ensemble Learning with Deep Branched Networks0
Online Representation Learning with Single and Multi-layer Hebbian Networks for Image Classification0
Learning Spatial Regularization with Image-level Supervisions for Multi-label Image ClassificationCode0
A Survey on Deep Learning in Medical Image Analysis0
EMNIST: an extension of MNIST to handwritten lettersCode0
A Novel Weight-Shared Multi-Stage CNN for Scale Robustness0
Empirical Risk Minimization for Stochastic Convex Optimization: O(1/n)- and O(1/n^2)-type of Risk Bounds0
Search Intelligence: Deep Learning For Dominant Category Prediction0
ImageNet MPEG-7 Visual Descriptors - Technical Report0
Fully Convolutional Architectures for Multi-Class Segmentation in Chest RadiographsCode0
Theoretical Foundations of Forward Feature Selection Methods based on Mutual Information0
CP-decomposition with Tensor Power Method for Convolutional Neural Networks CompressionCode0
Training Group Orthogonal Neural Networks with Privileged Information0
Dirty Pixels: Towards End-to-End Image Processing and PerceptionCode0
Residual and Plain Convolutional Neural Networks for 3D Brain MRI ClassificationCode0
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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