Papers with Code 아카이브
Face Detection
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Face Detection is a computer vision task that involves automatically identifying and locating human faces within digital images or videos. It is a fundamental technology that underpins many applications such as face recognition, face tracking, and facial analysis.
<span style="color:grey; opacity: 0.6">( Image credit: insightface )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Qengineering/LFFD-ncnn-Jetson-Nano
https://github.com/Qengineering/LFFD-ncnn-Raspberry-Pi-4
https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection
Face Detection with End-to-End Integration of a ConvNet and a 3D Model
https://github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetection
https://github.com/RuisongZhou/RetinaFace.pytorch
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/SSusantAchary/FaceDetection-counting-using-MTCNN
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/Saurav0074/Cartoon-Face-Detection-and-Recognition
Bringing Cartoons to Life: Towards Improved Cartoon Face Detection and Recognition Systems
https://github.com/SeungyounShin/EXTD
EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
https://github.com/ShiqiYu/libfacedetection
https://github.com/SmartEngines/stoppers_modelling
MIDV-2019: Challenges of the modern mobile-based document OCR
https://github.com/SohamSarfare/ADS
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/Speacer/Super-Resolution-Generative-Adversarial-Networks
https://github.com/StanislasBertrand/RetinaFace-tf2
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/StanislasBertrand/retinaface4j
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/Suaro/pidroid
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
https://github.com/Swybino/PotatoNet
https://github.com/Team-Neighborhood/awesome-face-detection
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/Tencent/FaceDetection-DSFD
https://github.com/Thehunk1206/Zero-DCE
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
https://github.com/TinDang97/face_recognition
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/TotoHugo/facedetection-lite-Outsystems
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
https://github.com/TropComplique/FaceBoxes-tensorflow
https://github.com/TropComplique/mtcnn-pytorch
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/WangChen0902/MTCNN-Paddle
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/WangChen0902/RetinaFace-Paddle
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/XiaXuehai/faceboxes
https://github.com/YonghaoHe/LFFD-A-Light-and-Fast-Face-Detector-for-Edge-Devices
https://github.com/ZHANG-SHI-CHANG/Pytorch_Retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/aannirajpatel/COMP562-Face-Mask-Detect
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/acnazarejr/fdet
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/afourast/avobjects
https://github.com/agrawalparth10/Face-is-the-Key
https://github.com/ajinkyabedekar/Face-to-Emoji
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/alexattia/ExtendedTinyFaces
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/alililia/ms_extend/tree/main/gpu_retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.