Facial Landmark Detection
47 papers with code • 9 benchmarks • 15 datasets
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 )
Benchmarks
These leaderboards are used to track progress in Facial Landmark Detection
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Libraries
Use these libraries to find Facial Landmark Detection models and implementations
300W
Helen
AFW
AFLW
LFPW
AFLW2000-3D
COFW
WFLW
COCO-WholeBody
300-VW
Latest papers with no code
LocalEyenet: Deep Attention framework for Localization of Eyes
The model architecture, build on stacked hourglass backbone, learns the self-attention in feature maps which aids in preserving global as well as local spatial dependencies in face image.
Neonatal Face and Facial Landmark Detection from Video Recordings
This paper explores automated face and facial landmark detection of neonates, which is an important first step in many video-based neonatal health applications, such as vital sign estimation, pain assessment, sleep-wake classification, and jaundice detection.
MATT: Multimodal Attention Level Estimation for e-learning Platforms
This work presents a new multimodal system for remote attention level estimation based on multimodal face analysis.
3D-Aware Facial Landmark Detection via Multi-View Consistent Training on Synthetic Data
Accurate facial landmark detection on wild images plays an essential role in human-computer interaction, entertainment, and medical applications.
Continuous Landmark Detection With 3D Queries
Neural networks for facial landmark detection are notoriously limited to a fixed set of landmarks in a dedicated layout, which must be specified at training time.
Domain Translation via Latent Space Mapping
In this paper, we investigate the problem of multi-domain translation: given an element $a$ of domain $A$, we would like to generate a corresponding $b$ sample in another domain $B$, and vice versa.
Towards Accurate Facial Landmark Detection via Cascaded Transformers
We formulate facial landmark detection as a coordinate regression task such that the model can be trained end-to-end.
RePFormer: Refinement Pyramid Transformer for Robust Facial Landmark Detection
This paper presents a Refinement Pyramid Transformer (RePFormer) for robust facial landmark detection.
Revisiting Facial Key Point Detection: An Efficient Approach Using Deep Neural Networks
The objective of the research has been to develop efficient deep learning models in terms of model size, parameters, and inference time and to study the effect of augmentation imputation and fine-tuning on these models.
Real-Time Facial Expression Recognition using Facial Landmarks and Neural Networks
Then, the human face is split into upper and lower faces, which enables the extraction of the desired features from each part.
