https://github.com/thesouthfrog/stylealign
공식 코드Aggregation via Separation: Boosting Facial Landmark Detector with Semi-Supervised Style Translation
Papers with Code 아카이브
Facial Landmark Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 3
- 평가표
- 10
- 보존된 평가 기록
- 38
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.
<span style="color:grey; opacity: 0.6">( Image credit: Style Aggregated Network for Facial Landmark Detection )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/unibas-gravis/parametric-face-image-generator
공식 코드https://github.com/vitoralbiero/img2pose
공식 코드img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation
https://github.com/wholebody3d/wholebody3d
공식 코드https://github.com/wywu/LAB
공식 코드https://github.com/xingzhehe/AutoLink-Self-supervised-Learning-of-Human-Skeletons-and-Object-Outlines-by-Linking-Keypoints
공식 코드AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints
https://github.com/xingzhehe/ganseg
공식 코드GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
https://github.com/yaojieliu/ICCVW2017-DenseFaceAlignment
공식 코드https://github.com/zhenglinzhou/star
공식 코드STAR Loss: Reducing Semantic Ambiguity in Facial Landmark Detection
https://github.com/zhiqic/keyposs
공식 코드KeyPosS: Plug-and-Play Facial Landmark Detection through GPS-Inspired True-Range Multilateration
https://github.com/163GitHub/AI
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HRNetW48_seg
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/AmrElsersy/PFLD-Pytorch-Landmarks
https://github.com/Burf/HRNetV2-OCR-Tensorflow2
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/CSAILVision/semantic-segmentation-pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/CompVis/unsupervised-part-segmentation
Unsupervised Part-Based Disentangling of Object Shape and Appearance
https://github.com/DELTA37/LatentKeypointGAN
https://github.com/HRNet/HRNet-FCOS
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/HRNet/HRNet-Facial-Landmark-Detection
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/HRNet/HRNet-Human-Pose-Estimation
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/HRNet/HRNet-Image-Classification
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/HRNet/HRNet-MaskRCNN-Benchmark
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/HRNet/HRNet-Object-Detection
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/HRNet/HRNet-Semantic-Segmentation
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/Human3DAIGC/AccurateFacialLandmarkDetection
Cascaded Dual Vision Transformer for Accurate Facial Landmark Detection
https://github.com/Jarr0d/Human-Parsing-Network
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/Mind23-2/MindCode-3/tree/main/HRNetW48_seg
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/MindSpore-scientific-2/code-9/tree/main/Deep_Feature_Factorization_For_Concept_Discovery
https://github.com/MindSpore-scientific/code-12/tree/main/Deep_Feature_Factorization_For_Concept_Discovery
https://github.com/NVIDIA/UnsupervisedLandmarkLearning
Unsupervised Part-Based Disentangling of Object Shape and Appearance
https://github.com/NVlabs/SCOPS
https://github.com/Ontheway361/pfld-pytorch
https://github.com/PaddlePaddle/PaddleClas
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/PaddlePaddle/PaddleDetection
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection
https://github.com/RomanticWithoutStatus/PFLD-TensorFlow2caffe
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.