https://github.com/yzyouzhang/AIR-ASVspoof
UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Towards Multi-domain Face Landmark Detection with Synthetic Data from Diffusion model
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks
FaceNet: A Unified Embedding for Face Recognition and Clustering
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance
BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs
Deep Alignment Network: A convolutional neural network for robust face alignment
Very Deep Convolutional Networks for Large-Scale Image Recognition
Weakly supervised discriminative feature learning with state information for person identification
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition
Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Inverse-Category-Frequency based supervised term weighting scheme for text categorization
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.