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/chenqikong/m3fas
공식 코드M3FAS: An Accurate and Robust MultiModal Mobile Face Anti-Spoofing System
https://github.com/chenzhe207/FDLSR
공식 코드Fisher Discriminative Least Squares Regression for Image Classification
https://github.com/chihfanhsu/fl_detection
공식 코드A Detailed Look At CNN-based Approaches In Facial Landmark Detection
https://github.com/choapinus/densenet10
공식 코드On the Feasibility of Creating Iris Periocular Morphed Images
https://github.com/choyingw/SynergyNet
공식 코드Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry
https://github.com/choyingw/Voice2Mesh
공식 코드Voice2Mesh: Cross-Modal 3D Face Model Generation from Voices
https://github.com/chrisdonahue/sdgan
공식 코드Semantically Decomposing the Latent Spaces of Generative Adversarial Networks
https://github.com/christianbv/AgeNet
공식 코드https://github.com/christophersims/fmri_adhd_classification
공식 코드Highly Accurate FMRI ADHD Classification using time distributed multi modal 3D CNNs
https://github.com/chuangchuangtan/c2p-clip-deepfakedetection
공식 코드C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detection
https://github.com/chuangchuangtan/data-independent-operator
공식 코드https://github.com/chuangchuangtan/freqnet-deepfakedetection
공식 코드Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Learning
https://github.com/chuangchuangtan/npr-deepfakedetection
공식 코드https://github.com/clad23/clad
공식 코드CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive Learning
https://github.com/cleardusk/3DDFA
공식 코드https://github.com/cleardusk/3DDFA_V2
공식 코드https://github.com/cleardusk/MFR
공식 코드https://github.com/cleardusk/MeGlass
공식 코드https://github.com/clferrari/facepartsswap
공식 코드What makes you, you? Analyzing Recognition by Swapping Face Parts
https://github.com/clks-wzz/FAS-SGTD
공식 코드Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing
https://github.com/clks-wzz/epcr
공식 코드https://github.com/clovaai/EXTD_Pytorch
공식 코드EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
https://github.com/clovaai/eresfd
공식 코드EResFD: Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detection
https://github.com/clpeng/Awesome-Face-Forgery-Generation-and-Detection
공식 코드Countering Malicious DeepFakes: Survey, Battleground, and Horizon
https://github.com/cmry/reap
공식 코드Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling
https://github.com/cnnlstm/fslsd_hires
공식 코드High-resolution Face Swapping via Latent Semantics Disentanglement
https://github.com/controlnet/av-deepfake1m
공식 코드AV-Deepfake1M: A Large-Scale LLM-Driven Audio-Visual Deepfake Dataset
https://github.com/coolEphemeroptera/AESRC2020
공식 코드https://github.com/crane-papercode/ICE-GAN
공식 코드https://github.com/croitorualin/biodeep
공식 코드Deepfake Media Generation and Detection in the Generative AI Era: A Survey and Outlook
https://github.com/cruiseyugh/gus
공식 코드https://github.com/crusnic-corp/BN-AuthProf
공식 코드BN-AuthProf: Benchmarking Machine Learning for Bangla Author Profiling on Social Media Texts
https://github.com/crywang/RFM
공식 코드https://github.com/csehong/SSPP-DAN
공식 코드SSPP-DAN: Deep Domain Adaptation Network for Face Recognition with Single Sample Per Person
https://github.com/csinva/matching-with-gans
공식 코드Matched sample selection with GANs for mitigating attribute confounding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.