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 5201–5250 of 10420 papers

TitleStatusHype
Transfer Learning with Kernel Methods—0
Reduce, Reuse, Recycle: Improving Training Efficiency with Distillation—0
Improving Fairness in Image Classification via SketchingCode0
IM-Loss: Information Maximization Loss for Spiking Neural Networks—0
SAGE: Saliency-Guided Mixup with Optimal Rearrangements—0
Generative Negative Text Replay for Continual Vision-Language Pretraining—0
Studying inductive biases in image classification task—0
FI-ODE: Certifiably Robust Forward Invariance in Neural ODEsCode0
IM: An R-Package for Computation of Image Moments and Moment Invariants—0
Distributed Black-box Attack: Do Not Overestimate Black-box AttacksCode0
Improving Chest X-Ray Classification by RNN-based Patient Monitoring—0
Grafting Vision Transformers—0
Contextual Learning in Fourier Complex Field for VHR Remote Sensing ImagesCode0
Learning Location from Shared Elevation Profiles in Fitness Apps: A Privacy Perspective—0
Poisson Reweighted Laplacian Uncertainty Sampling for Graph-based Active LearningCode0
Leveraging Computer Vision Application in Visual Arts: A Case Study on the Use of Residual Neural Network to Classify and Analyze Baroque Paintings—0
Neural Networks with Quantization ConstraintsCode0
Text2Model: Text-based Model Induction for Zero-shot Image Classification—0
Jointly Resampling and Reconstructing Corrupted Images for Image Classification using Frequency-Selective Mesh-to-Grid Resampling—0
A Generic Shared Attention Mechanism for Various Backbone Neural Networks—0
UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification—0
Geo-SIC: Learning Deformable Geometric Shapes in Deep Image ClassifiersCode0
Provably Learning Diverse Features in Multi-View Data with Midpoint MixupCode0
Analyzing the Use of Influence Functions for Instance-Specific Data Filtering in Neural Machine Translation—0
Collaborative Image Understanding—0
Efficient Automatic Machine Learning via Design GraphsCode0
Imbalanced Classification in Medical Imaging via Regrouping—0
Iterative collaborative routing among equivariant capsules for transformation-robust capsule networks—0
Visual-Semantic Contrastive Alignment for Few-Shot Image Classification—0
Robustcaps: a transformation-robust capsule network for image classification—0
Similarity of Neural Architectures using Adversarial Attack Transferability—0
Analysing Training-Data Leakage from Gradients through Linear Systems and Gradient MatchingCode0
G2NetPL: Generic Game-Theoretic Network for Partial-Label Image Classification—0
Efficient, probabilistic analysis of combinatorial neural codes—0
Training set cleansing of backdoor poisoning by self-supervised representation learning—0
Sustainable Personalisation and Explainability in Dyadic Data Systems—0
A Unified View of Masked Image ModelingCode0
On effects of Knowledge Distillation on Transfer Learning—0
Layer-wise Relevance Propagation for Echo State Networks applied to Earth System Variability—0
Few-Shot Learning of Compact Models via Task-Specific Meta Distillation—0
A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information—0
Packed-Ensembles for Efficient Uncertainty Estimation—0
Early Diagnosis of Retinal Blood Vessel Damage via Deep Learning-Powered Collective Intelligence ModelsCode0
Signal Processing for Implicit Neural Representations—0
Bootstrapping the Relationship Between Images and Their Clean and Noisy LabelsCode0
Explaining Image Classification with Visual DebatesCode0
Self-Supervised Learning Through Efference CopiesCode0
Histopathological Image Classification based on Self-Supervised Vision Transformer and Weak LabelsCode0
Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated LearningCode0
Federated Learning with Privacy-Preserving Ensemble Attention Distillation—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