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/cydonia999/VGGFace2-pytorch
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/darkAlert/retinafacert
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/dengpingfan/fsgan
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/dheerajsingh7351/facedetect
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/discipleofhamilton/RetinaFace
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/dl-maxwang/blazeface-tensorflow
BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
https://github.com/do4am/MultiviewFaceDetector
Multi-view Face Detection Using Deep Convolutional Neural Networks
https://github.com/donnyyou/pytorch-lffd
https://github.com/elliottzheng/face-detection
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/embracesource-cv-com/FCHD
https://github.com/eric-erki/ID-Card-Segmentation
https://github.com/esimov/pigo
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
https://github.com/espressif/esp-who
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/faridSam/srn
Selective Refinement Network for High Performance Face Detection
https://github.com/foxer9developer/Face-Emotion-to-Emoji-Convertor
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/getcontrol/KYC-tensorflow
https://github.com/getcontrol/KYC-train-model
https://github.com/glarbi/Face-detection
Selective Refinement Network for High Performance Face Detection
https://github.com/gmlunesa/detectfacemask
https://github.com/goingqs/pyramidbox
https://github.com/gouthamvgk/facemesh_coreml_tf
https://github.com/gpspelle/Crowd-Counting
https://github.com/grip-unina/GANimageDetection
AnimalWeb: A Large-Scale Hierarchical Dataset of Annotated Animal Faces
https://github.com/gscdit/Mood-Analysis
Real-time Convolutional Neural Networks for Emotion and Gender Classification
https://github.com/guppykang/joshFaceV2
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/gurushantj/MTCNN
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
https://github.com/hggym/pigo
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
https://github.com/hhj1897/face_detection
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/hollance/BlazeFace-PyTorch
BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
https://github.com/hqhoangvuong/paperspace_ml_01
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/huangshenneng/padd_retinaface
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/hukkelas/DSFD-Pytorch-Inference
https://github.com/iChenning/facedetection
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/ibadr/RetinaFace
RetinaFace: Single-stage Dense Face Localisation in the Wild
https://github.com/icey-zhang/MTCNN_paddle
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.