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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 10251–10300 of 10420 papers

TitleStatusHype
Transferring Rich Feature Hierarchies for Robust Visual Tracking—0
Image classification by visual bag-of-words refinement and reduction—0
Sparse Deep Stacking Network for Image Classification—0
Improved texture image classification through the use of a corrosion-inspired cellular automaton—0
Unsupervised Feature Learning with C-SVDDNet—0
Half-CNN: A General Framework for Whole-Image Regression—0
Learning Activation Functions to Improve Deep Neural NetworksCode0
Striving for Simplicity: The All Convolutional NetCode0
Visualizing and Comparing Convolutional Neural Networks—0
An Analysis of Unsupervised Pre-training in Light of Recent AdvancesCode0
Automatic Discovery and Optimization of Parts for Image Classification—0
Deep learning with Elastic Averaging SGDCode0
Data Representation using the Weyl Transform—0
Fractional Max-PoolingCode0
Compressing Deep Convolutional Networks using Vector Quantization—0
Sparse, guided feature connections in an Abstract Deep Network—0
Highly Efficient Forward and Backward Propagation of Convolutional Neural Networks for Pixelwise Classification—0
Object-centric Sampling for Fine-grained Image Classification—0
HyperSpectral classification with adaptively weighted L1-norm regularization and spatial postprocessing—0
Hashing on Nonlinear Manifolds—0
Discriminative Unsupervised Feature Learning with Convolutional Neural NetworksCode0
Graph Clustering With Missing Data: Convex Algorithms and Analysis—0
Predicting Useful Neighborhoods for Lazy Local Learning—0
Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces—0
Self-Adaptable Templates for Feature Coding—0
Zeta Hull Pursuits: Learning Nonconvex Data Hulls—0
Untangling Local and Global Deformations in Deep Convolutional Networks for Image Classification and Sliding Window Detection—0
The Treasure beneath Convolutional Layers: Cross-convolutional-layer Pooling for Image ClassificationCode0
Image Classification and Retrieval from User-Supplied Tags—0
Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors—0
The Application of Two-level Attention Models in Deep Convolutional Neural Network for Fine-grained Image Classification—0
Do Convnets Learn Correspondence?—0
Generalized Adaptive Dictionary Learning via Domain Shift Minimization—0
A comparison of dense region detectors for image search and fine-grained classification—0
Remote sensing image classification exploiting multiple kernel learning—0
KCRC-LCD: Discriminative Kernel Collaborative Representation with Locality Constrained Dictionary for Visual Categorization—0
HD-CNN: Hierarchical Deep Convolutional Neural Network for Large Scale Visual RecognitionCode0
Term-Weighting Learning via Genetic Programming for Text Classification—0
Evaluation of Output Embeddings for Fine-Grained Image ClassificationCode0
Efficient multivariate sequence classification—0
Image Classification with A Deep Network Model based on Compressive Sensing—0
Deep Learning Representation using Autoencoder for 3D Shape Retrieval—0
Do More Dropouts in Pool5 Feature Maps for Better Object Detection—0
Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification—0
Spatially-sparse convolutional neural networksCode0
Deeply-Supervised NetsCode0
Compute Less to Get More: Using ORC to Improve Sparse Filtering—0
A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data—0
10,000+ Times Accelerated Robust Subset Selection (ARSS)—0
Image Retrieval And Classification Using Local Feature Vectors—0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10RevCol-HTop 1 Accuracy90—Unverified