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 10261050 of 10419 papers

TitleStatusHype
Progress and limitations of deep networks to recognize objects in unusual posesCode1
Tree Structure-Aware Few-Shot Image Classification via Hierarchical AggregationCode1
LightViT: Towards Light-Weight Convolution-Free Vision TransformersCode1
UniNet: Unified Architecture Search with Convolution, Transformer, and MLPCode1
Contrastive Deep SupervisionCode1
Regression Metric Loss: Learning a Semantic Representation Space for Medical ImagesCode1
Backdoor Attacks on Crowd CountingCode1
Towards a More Rigorous Science of Blindspot Discovery in Image Classification ModelsCode1
DLME: Deep Local-flatness Manifold EmbeddingCode1
ReMix: A General and Efficient Framework for Multiple Instance Learning based Whole Slide Image ClassificationCode1
DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot LearningCode1
CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN ExecutionCode1
FlowNAS: Neural Architecture Search for Optical Flow EstimationCode1
NP-Match: When Neural Processes meet Semi-Supervised LearningCode1
Saliency-Regularized Deep Multi-Task LearningCode1
Can Language Understand Depth?Code1
Test-time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution ShiftCode1
Learning Cross-Image Object Semantic Relation in Transformer for Few-Shot Fine-Grained Image ClassificationCode1
BadHash: Invisible Backdoor Attacks against Deep Hashing with Clean LabelCode1
Learning Iterative Reasoning through Energy MinimizationCode1
Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image ClassificationCode1
Revisiting Label Smoothing and Knowledge Distillation Compatibility: What was Missing?Code1
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image ClassificationCode1
RevBiFPN: The Fully Reversible Bidirectional Feature Pyramid NetworkCode1
Robustifying Vision Transformer without Retraining from Scratch by Test-Time Class-Conditional Feature AlignmentCode1
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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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 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