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 2351–2375 of 10420 papers

TitleStatusHype
What do larger image classifiers memorise?—0
Progressive Neural Compression for Adaptive Image Offloading under Timing ConstraintsCode1
Enhancing Representations through Heterogeneous Self-Supervised Learning—0
Tight Certified Robustness via Min-Max Representations of ReLU Neural Networks—0
Activate and Reject: Towards Safe Domain Generalization under Category Shift—0
PriViT: Vision Transformers for Fast Private InferenceCode0
A privacy-preserving method using secret key for convolutional neural network-based speech classification—0
Why Do We Need Weight Decay in Modern Deep Learning?Code1
TiC: Exploring Vision Transformer in ConvolutionCode1
PrototypeFormer: Learning to Explore Prototype Relationships for Few-shot Image Classification—0
Improved Baselines with Visual Instruction TuningCode6
DED: Diagnostic Evidence Distillation for acne severity grading on face imagesCode0
PDR-CapsNet: an Energy-Efficient Parallel Approach to Dynamic Routing in Capsule Networks—0
Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models—0
Comparative Analysis of Imbalanced Malware Byteplot Image Classification using Transfer Learning—0
Dynamic Shuffle: An Efficient Channel Mixture Method—0
Deformation-Invariant Neural Network and Its Applications in Distorted Image Restoration and Analysis—0
IBCL: Zero-shot Model Generation for Task Trade-offs in Continual LearningCode0
ViT-ReciproCAM: Gradient and Attention-Free Visual Explanations for Vision TransformerCode1
Neural architecture impact on identifying temporally extended Reinforcement Learning tasks—0
Heterogeneous Federated Learning Using Knowledge Codistillation—0
SemiReward: A General Reward Model for Semi-supervised LearningCode1
Inductive biases of multi-task learning and finetuning: multiple regimes of feature reuseCode0
Approximately Equivariant Quantum Neural Network for p4m Group Symmetries in Images—0
RoFormer for Position Aware Multiple Instance Learning in Whole Slide Image ClassificationCode0
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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