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/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
https://github.com/xinqi-fan/ABAW2021
공식 코드Spatial and Temporal Networks for Facial Expression Recognition in the Wild Videos
https://github.com/xiyinmsu/MultiTask-CNN
공식 코드Multi-Task Convolutional Neural Network for Pose-Invariant Face Recognition
https://github.com/xjchengit/singgraph
공식 코드https://github.com/xjtupanda/auw-gcn
공식 코드AU-aware graph convolutional network for Macro- and Micro-expression spotting
https://github.com/xk-huang/OrdinalCLIP
공식 코드OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression
https://github.com/xmba15/ai4eo_map_your_city
공식 코드Building Age Estimation: A New Multi-Modal Benchmark Dataset and Community Challenge
https://github.com/xmed-lab/ucvme
공식 코드https://github.com/xtinkt/editable
공식 코드https://github.com/xuyingzhongguo/deepfakeannotations
공식 코드Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
https://github.com/xuyingzhongguo/mcx-api
공식 코드Learning Pairwise Interaction for Generalizable DeepFake Detection
https://github.com/xuyingzhongguo/vod
공식 코드VoD: Learning Volume of Differences for Video-Based Deepfake Detection
https://github.com/xxtars/emo-llama
공식 코드EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction Tuning
https://github.com/ya332/robust_sleepnets
공식 코드https://github.com/yafuly/deepfaketextdetect
공식 코드https://github.com/yafuly/mage
공식 코드https://github.com/yaoing/dan
공식 코드Distract Your Attention: Multi-head Cross Attention Network for Facial Expression Recognition
https://github.com/yaojieliu/CVPR2019-DeepTreeLearningForZeroShotFaceAntispoofing
공식 코드https://github.com/yaojieliu/ICCVW2017-DenseFaceAlignment
공식 코드https://github.com/yaselley/ssl_layerwise_deepfake
공식 코드Comprehensive Layer-wise Analysis of SSL Models for Audio Deepfake Detection
https://github.com/ydc123/Dark_Surrogate_Model
공식 코드Boosting the Adversarial Transferability of Surrogate Models with Dark Knowledge
https://github.com/ydwen/opensphere/blob/main/opensphere/module/head/simple.py
공식 코드https://github.com/yelboudouri/EmoNeXt
공식 코드https://github.com/yerfor/Real3DPortrait
공식 코드Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.