https://github.com/MindCode-4/code-14/tree/main/Zero-DCE%2B%2B
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
Papers with Code 아카이브
Facial Recognition and Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Facial tasks in machine learning operate based on images or video frames (or other datasets) focussed on human faces.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MindCode-4/code-4/tree/main/rembert
https://github.com/MindCode-4/code-5/tree/main/wavlm
https://github.com/MindCode-4/code-6/tree/main/circle-loss
Circle Loss: A Unified Perspective of Pair Similarity Optimization
https://github.com/MindSpore-paper-code-2/code2/tree/main/PGAN
Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/MindSpore-paper-code-2/code2/tree/main/PyramidBox
PyramidBox++: High Performance Detector for Finding Tiny Face
https://github.com/MindSpore-paper-code-2/code2/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/MindSpore-paper-code-2/code3/tree/main/STPM
Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
https://github.com/MindSpore-paper-code-2/code3/tree/main/ssd_resnet34
https://github.com/MindSpore-paper-code-3/code2/tree/main/DeepID
https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceAttribute
https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceDetection
Face Detection with End-to-End Integration of a ConvNet and a 3D Model
https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceRecognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/MindSpore-paper-code-3/code3/tree/main/FaceRecognitionForTracking
https://github.com/MindSpore-paper-code-3/code4/tree/main/HiFaceGAN
HiFaceGAN: Face Renovation via Collaborative Suppression and Replenishment
https://github.com/MindSpore-paper-code-3/code5/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/MindSpore-paper-code-3/code5/tree/main/resnet50_adv_pruning
https://github.com/MindSpore-paper-code-3/code5/tree/main/retinanet_resnet101
https://github.com/MindSpore-paper-code-3/code5/tree/main/retinanet_resnet152
https://github.com/MindSpore-paper-code-3/code6/tree/main/ADNet
ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
https://github.com/MindSpore-paper-code-3/code6/tree/main/cct
https://github.com/MindSpore-paper-code-3/code6/tree/main/cdp
Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition
https://github.com/MindSpore-paper-code-3/code6/tree/main/centerface
CenterFace: Joint Face Detection and Alignment Using Face as Point
https://github.com/MindSpore-paper-code-3/code7/tree/main/FaceAttribute
https://github.com/MindSpore-paper-code-3/code7/tree/main/FaceDetection
Face Detection with End-to-End Integration of a ConvNet and a 3D Model
https://github.com/MindSpore-paper-code-3/code7/tree/main/FaceRecognition
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/MindSpore-paper-code-3/code7/tree/main/FaceRecognitionForTracking
https://github.com/MindSpore-paper-code-3/code7/tree/main/faceboxes
https://github.com/MindSpore-paper-code-3/code8/tree/main/DeepID
https://github.com/MindSpore-paper-code-3/code8/tree/main/FaceAttribute
https://github.com/MindSpore-paper-code-3/code8/tree/main/FaceDetection
Face Detection with End-to-End Integration of a ConvNet and a 3D Model
https://github.com/MindSpore-paper-code-3/code8/tree/main/FaceRecognition
https://github.com/MindSpore-paper-code-3/code8/tree/main/FaceRecognitionForTracking
https://github.com/MindSpore-paper-code-3/code8/tree/main/faceboxes
FaceNet: A Unified Embedding for Face Recognition and Clustering
https://github.com/MindSpore-paper-code-3/code9/tree/main/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/MindSpore-paper-code-3/code9/tree/main/PointNet2
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.