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 7801–7850 of 10420 papers

TitleStatusHype
Deep Ensemble Bayesian Active Learning : Adressing the Mode Collapse issue in Monte Carlo dropout via Ensembles—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
Improving the Accuracy of Learning Example Weights for Imbalance Classification—0
Improving Tail-Class Representation with Centroid Contrastive Learning—0
Improving Strong-Scaling of CNN Training by Exploiting Finer-Grained Parallelism—0
Improving STDP-based Visual Feature Learning with Whitening—0
DeepEMD: Few-Shot Image Classification With Differentiable Earth Mover's Distance and Structured Classifiers—0
Auxiliary Multimodal LSTM for Audio-visual Speech Recognition and Lipreading—0
Altogether: Image Captioning via Re-aligning Alt-text—0
Adaptive Data Augmentation with Deep Parallel Generative Models—0
Accurate and Efficient Similarity Search for Large Scale Face Recognition—0
Improving Feature Stability during Upsampling -- Spectral Artifacts and the Importance of Spatial Context—0
Deep Elastic Networks with Model Selection for Multi-Task Learning—0
Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classification—0
Auxiliary Learning by Implicit Differentiation—0
Improving Sample Complexity with Observational Supervision—0
Deep Domain Generalization with Feature-norm Network—0
Recent Advances in Convolutional Neural Network Acceleration—0
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations—0
Recent Advances in Embedding Methods for Multi-Object Tracking: A Survey—0
Deep Discriminative Learning for Unsupervised Domain Adaptation—0
Recent Developments from Attribute Profiles for Remote Sensing Image Classification—0
Auxiliary Image Regularization for Deep CNNs with Noisy Labels—0
Alternating Multi-bit Quantization for Recurrent Neural Networks—0
Improving Robustness and Reliability in Medical Image Classification with Latent-Guided Diffusion and Nested-Ensembles—0
ReCLIP: A Strong Zero-Shot Baseline for Referring Expression Comprehension—0
Robust Contrastive Active Learning with Feature-guided Query Strategies—0
Deep Dictionary Learning: A PARametric NETwork Approach—0
RecNets: Channel-wise Recurrent Convolutional Neural Networks—0
Recognizing Image Objects by Relational Analysis Using Heterogeneous Superpixels and Deep Convolutional Features—0
Recognizing Images with at most one Spike per Neuron—0
Improving Resnet-9 Generalization Trained on Small Datasets—0
Deep Dependency Networks for Multi-Label Classification—0
Improving Quaternion Neural Networks with Quaternionic Activation Functions—0
Deep Degradation Prior for Low-Quality Image Classification—0
Deep Decision Network for Multi-Class Image Classification—0
Reconstruction Regularized Deep Metric Learning for Multi-label Image Classification—0
Auxiliary Class Based Multiple Choice Learning—0
Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception—0
Improving plant disease classification by adaptive minimal ensembling—0
Recovering Localized Adversarial Attacks—0
Rectified Meta-Learning from Noisy Labels for Robust Image-based Plant Disease Diagnosis—0
Improving Performance of Semi-Supervised Learning by Adversarial Attacks—0
Deep Curriculum Learning for PolSAR Image Classification—0
Recurrent Attention Unit—0
Improving Object Detection with Selective Self-supervised Self-training—0
Deep Co-Space: Sample Mining Across Feature Transformation for Semi-Supervised Learning—0
Improving Normalization with the James-Stein Estimator—0
Recurrently Exploring Class-wise Attention in A Hybrid Convolutional and Bidirectional LSTM Network for Multi-label Aerial Image Classification—0
Auto-view contrastive learning for few-shot image recognition—0
Show:102550
← PrevPage 157 of 209Next →
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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified