https://github.com/wildchlamydia/mivolo
공식 코드MiVOLO: Multi-input Transformer for Age and Gender Estimation
Papers with Code 아카이브
3D Face Reconstruction
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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>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/williamyang1991/vtoonify
공식 코드VToonify: Controllable High-Resolution Portrait Video Style Transfer
https://github.com/winfredy/sadtalker
공식 코드https://github.com/wkabbani/sclera-segmentation
공식 코드Robust Sclera Segmentation for Skin-tone Agnostic Face Image Quality Assessment
https://github.com/wolo-wolo/FFR_FD-Effective-and-Fast-Detection-of-DeepFakes-Based-on-Feature-Point-Defects
공식 코드FFR_FD: Effective and Fast Detection of DeepFakes Based on Feature Point Defects
https://github.com/wolo-wolo/FSFM
공식 코드https://github.com/wq2012/kPCA
공식 코드Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape Models
https://github.com/wtomin/Multitask-Emotion-Recognition-with-Incomplete-Labels
공식 코드https://github.com/wuhaozhe/style_avatar
공식 코드Imitating Arbitrary Talking Style for Realistic Audio-DrivenTalking Face Synthesis
https://github.com/wuqiuche/micromotion-stylegan
공식 코드https://github.com/wuyangluo/reffaceinpainting
공식 코드Reference-Guided Large-Scale Face Inpainting with Identity and Texture Control
https://github.com/wuzipengyl/itarget-interpretable-tailored-age-regression-for-grouped-epigenetic-traits
공식 코드iTARGET: Interpretable Tailored Age Regression for Grouped Epigenetic Traits
https://github.com/wxzyd123/pivotal_objective_perturbation
공식 코드Mitigating Unauthorized Speech Synthesis for Voice Protection
https://github.com/wxzyd123/safespeech
공식 코드SafeSpeech: Robust and Universal Voice Protection Against Malicious Speech Synthesis
https://github.com/wy1iu/sphereface
공식 코드https://github.com/wykstc/MERC-main
공식 코드Joyful: Joint Modality Fusion and Graph Contrastive Learning for Multimodal Emotion Recognition
https://github.com/wywu/LAB
공식 코드https://github.com/wywu/ReenactGAN
공식 코드https://github.com/wzhouxiff/restoreformer
공식 코드RestoreFormer: High-Quality Blind Face Restoration from Undegraded Key-Value Pairs
https://github.com/wznpub/MMA_Regularization
공식 코드MMA Regularization: Decorrelating Weights of Neural Networks by Maximizing the Minimal Angles
https://github.com/xf1994/ECML
공식 코드ECML: An Ensemble Cascade Metric Learning Mechanism towards Face Verification
https://github.com/xhp-hust-2018-2011/dcreg
공식 코드https://github.com/xianhua-he/cvpr2024-face-anti-spoofing-challenge
공식 코드Joint Physical-Digital Facial Attack Detection Via Simulating Spoofing Clues
https://github.com/xianyunsun/vra
공식 코드https://github.com/xiaoboCASIA/SV-X-Softmax
공식 코드https://github.com/xiaojie1017/Human-Parts
공식 코드https://github.com/xieyuankun/Codecfake
공식 코드The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake Audio
https://github.com/xieyuankun/all-type-add
공식 코드Detect All-Type Deepfake Audio: Wavelet Prompt Tuning for Enhanced Auditory Perception
https://github.com/xieyuankun/alm-add
공식 코드Does Current Deepfake Audio Detection Model Effectively Detect ALM-based Deepfake Audio?
https://github.com/xieyuankun/fsd-dataset
공식 코드https://github.com/xieyuankun/st-codecfake
공식 코드Neural Codec Source Tracing: Toward Comprehensive Attribution in Open-Set Condition
https://github.com/xieyuankun/tdl-add
공식 코드https://github.com/xilin1991/Large-scale-Multi-illumination-HR-Database
공식 코드Image Enhancement for Remote Photoplethysmography in a Low-Light Environment
https://github.com/xingzhehe/AutoLink-Self-supervised-Learning-of-Human-Skeletons-and-Object-Outlines-by-Linking-Keypoints
공식 코드AutoLink: Self-supervised Learning of Human Skeletons and Object Outlines by Linking Keypoints
https://github.com/xingzhehe/ganseg
공식 코드GANSeg: Learning to Segment by Unsupervised Hierarchical Image Generation
https://github.com/xinntao/ESRGAN
공식 코드ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.