SOTAVerified

Facial Landmark Detection

Facial Landmark Detection is a computer vision task that involves detecting and localizing specific points or landmarks on a face, such as the eyes, nose, mouth, and chin. The goal is to accurately identify these landmarks in images or videos of faces in real-time and use them for various applications, such as face recognition, facial expression analysis, and head pose estimation.

( Image credit: Style Aggregated Network for Facial Landmark Detection )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 139 papers

TitleStatusHype
MOL: Joint Estimation of Micro-Expression, Optical Flow, and Landmark via Transformer-Graph-Style ConvolutionCode1
Semantic Style Transfer for Enhancing Animal Facial Landmark Detection—0
ORFormer: Occlusion-Robust Transformer for Accurate Facial Landmark Detection—0
Precise Facial Landmark Detection by Dynamic Semantic Aggregation TransformerCode0
Cascaded Dual Vision Transformer for Accurate Facial Landmark DetectionCode0
POPoS: Improving Efficient and Robust Facial Landmark Detection with Parallel Optimal Position SearchCode0
Toward Scalable Image Feature Compression: A Content-Adaptive and Diffusion-Based Approach—0
Real-Time Drowsiness Detection Using Eye Aspect Ratio and Facial Landmark Detection—0
Efficient Facial Landmark Detection for Embedded Systems—0
Infinite 3D Landmarks: Improving Continuous 2D Facial Landmark Detection—0
Show:102550
← PrevPage 1 of 14Next →
All datasets300WCOCO-WholeBodyAFLW-FullAFLW-FrontCatFLWWFLW300-VW (C)300W (Full)COFWAFLW2000-3D

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DCFE (Box height Norm, 19 landmarks - no earlobs)Mean NME 2.17—Unverified
23DDE (Box height Norm, 19 landmarks - no earlobs)Mean NME2.01—Unverified
3SANMean NME 1.91—Unverified
4AnchorFaceMean NME 1.56—Unverified
5FiFAMean NME 0.92—Unverified