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

Showing 110 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 Detection0
ORFormer: Occlusion-Robust Transformer for Accurate Facial Landmark Detection0
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 Approach0
Real-Time Drowsiness Detection Using Eye Aspect Ratio and Facial Landmark Detection0
Efficient Facial Landmark Detection for Embedded Systems0
Infinite 3D Landmarks: Improving Continuous 2D Facial Landmark Detection0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SANMean NME 1.85Unverified
2AnchorFaceMean NME1.38Unverified
3FiFAMean NME0.8Unverified