https://github.com/germino-liuhe/dsat
공식 코드Precise Facial Landmark Detection by Dynamic Semantic Aggregation Transformer
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/gewanying/shap-anti-spoofing
공식 코드Explainable deepfake and spoofing detection: an attack analysis using SHapley Additive exPlanations
https://github.com/gilikn/fakeout
공식 코드FakeOut: Leveraging Out-of-domain Self-supervision for Multi-modal Video Deepfake Detection
https://github.com/gist-ailab/teaching-where-to-look
공식 코드https://github.com/git-disl/Chameleon
공식 코드Personalized Privacy Protection Mask Against Unauthorized Facial Recognition
https://github.com/gkaradzhov/ClickbaitRANLP
공식 코드We Built a Fake News & Click-bait Filter: What Happened Next Will Blow Your Mind!
https://github.com/gojasper/flash-diffusion
공식 코드Flash Diffusion: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation
https://github.com/golnazghiasi/cofw68-benchmark
공식 코드Occlusion Coherence: Detecting and Localizing Occluded Faces
https://github.com/golnazghiasi/hpm-detection-code
공식 코드Occlusion Coherence: Detecting and Localizing Occluded Faces
https://github.com/gongsixue/DebFace
공식 코드Jointly De-biasing Face Recognition and Demographic Attribute Estimation
https://github.com/gonyrosenman/tff
공식 코드https://github.com/grigorisg9gr/deformable_tracking_review_ijcv2016
공식 코드A Comprehensive Performance Evaluation of Deformable Face Tracking "In-the-Wild"
https://github.com/grigorisg9gr/polynomial_nets
공식 코드https://github.com/grip-unina/id-reveal
공식 코드https://github.com/grip-unina/poi-forensics
공식 코드https://github.com/gsethan17/CAPNet_ABAW2021
공식 코드Causal affect prediction model using a facial image sequence
https://github.com/guanghaozhu663/skd-tstsan
공식 코드https://github.com/guanjiyang/sac_jc
공식 코드https://github.com/gufranSabri/FSBI
공식 코드FSBI: Deepfakes Detection with Frequency Enhanced Self-Blended Images
https://github.com/guillermogotre/cusp
공식 코드https://github.com/guoyang9/class-imbalance-VQA
공식 코드Loss re-scaling VQA: Revisiting the LanguagePrior Problem from a Class-imbalance View
https://github.com/guoyurong0104/crl-code
공식 코드Competing Ratio Loss for Discriminative Multi-class Image Classification
https://github.com/gurayozgur/foundpad
공식 코드FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection
https://github.com/gurayozgur/madation
공식 코드MADation: Face Morphing Attack Detection with Foundation Models
https://github.com/gy20073/compact_bilinear_pooling
공식 코드https://github.com/gyh5421/unified_deep_clustering
공식 코드https://github.com/hadushhailu/daal-dml
공식 코드DAAL: Density-Aware Adaptive Line Margin Loss for Multi-Modal Deep Metric Learning
https://github.com/haibo-qiu/SynFace
공식 코드https://github.com/haibo-qiu/from
공식 코드End2End Occluded Face Recognition by Masking Corrupted Features
https://github.com/haiyuwu/ba-test-dataset
공식 코드What Should Be Balanced in a "Balanced" Face Recognition Dataset?
https://github.com/haiyuwu/celebamso
공식 코드https://github.com/haiyuwu/facebrightness
공식 코드Face Recognition Accuracy Across Demographics: Shining a Light Into the Problem
https://github.com/haiyuwu/logicalconsistency
공식 코드Logical Consistency and Greater Descriptive Power for Facial Hair Attribute Learning
https://github.com/haiyuwu/sota-face-recognition-train-and-test
공식 코드https://github.com/halmstaduniversitybiometrics/lfw-beautified
공식 코드LFW-Beautified: A Dataset of Face Images with Beautification and Augmented Reality Filters
https://github.com/hamzah-luqman/mfr
공식 코드Ensemble Learning using Transformers and Convolutional Networks for Masked Face Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.