https://github.com/TangrisJones/AI-dfa
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Face reconstruction is the task of recovering the facial geometry of a face from an image.
<span style="color:grey; opacity: 0.6">( Image credit: Microsoft Deep3DFaceReconstruction )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
DeepFaceLab: Integrated, flexible and extensible face-swapping framework
Very Deep Convolutional Networks for Large-Scale Image Recognition
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
FaceNet: A Unified Embedding for Face Recognition and Clustering
Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
Circle Loss: A Unified Perspective of Pair Similarity Optimization
Very Deep Convolutional Networks for Large-Scale Image Recognition
Object Detection with Pixel Intensity Comparisons Organized in Decision Trees
FaceNet: A Unified Embedding for Face Recognition and Clustering
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks
Improving the Transferability of Targeted Adversarial Examples through Object-Based Diverse Input
Federated Learning for Face Recognition with Gradient Correction
Very Deep Convolutional Networks for Large-Scale Image Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.