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/kuhnkeF/ABAW2020TNT
공식 코드https://github.com/kunkunlin1221/InstructFLIP
공식 코드InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofing
https://github.com/kwanyun/FFaceNeRF
공식 코드https://github.com/kwanyun/LeGO_code
공식 코드https://github.com/kwanyun/StyleSketch
공식 코드Stylized Face Sketch Extraction via Generative Prior with Limited Data
https://github.com/l8cv/busterx
공식 코드BusterX: MLLM-Powered AI-Generated Video Forgery Detection and Explanation
https://github.com/laiyingxin2/dadf
공식 코드Detect Any Deepfakes: Segment Anything Meets Face Forgery Detection and Localization
https://github.com/laiyingxin2/gm-df
공식 코드https://github.com/laiyingxin2/shield
공식 코드https://github.com/lalithbharadwajbaru/wavelet-clip
공식 코드Wavelet-Driven Generalizable Framework for Deepfake Face Forgery Detection
https://github.com/langlrsw/AAL-unbiased-authentication
공식 코드https://github.com/lattas/avatarme
공식 코드AvatarMe: Realistically Renderable 3D Facial Reconstruction "in-the-wild"
https://github.com/leaffeall/DFS-GDD
공식 코드Decoupling Forgery Semantics for Generalizable Deepfake Detection
https://github.com/learninginvision/spu
공식 코드Self-Paced Deep Regression Forests with Consideration of Ranking Fairness
https://github.com/leebebeto/inter-prototype
공식 코드Improving Face Recognition with Large Age Gaps by Learning to Distinguish Children
https://github.com/leeisack/latent-ofer
공식 코드https://github.com/lehinevych/SAAN
공식 코드Self-attention aggregation network for video face representation and recognition
https://github.com/lelechen63/Talking-head-Generation-with-Rhythmic-Head-Motion
공식 코드https://github.com/lelechen63/talking-head-generation-survey
공식 코드What comprises a good talking-head video generation?: A Survey and Benchmark
https://github.com/leminhbinh0209/add
공식 코드https://github.com/leminhbinh0209/cvpr24-fas
공식 코드https://github.com/lemuelpuglisi/synthba
공식 코드SynthBA: Reliable Brain Age Estimation Across Multiple MRI Sequences and Resolutions
https://github.com/leo7r/swiftface
공식 코드https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
공식 코드High-Resolution Representations for Labeling Pixels and Regions
https://github.com/lexieyang/face_img_inpainting
공식 코드https://github.com/lhyfst/dsfnet
공식 코드DSFNet: Dual Space Fusion Network for Occlusion-Robust 3D Dense Face Alignment
https://github.com/li-8023/multi-function-face-recognition
공식 코드https://github.com/li-wanhua/label2label
공식 코드Label2Label: A Language Modeling Framework for Multi-Attribute Learning
https://github.com/liangchen527/sladd
공식 코드Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection
https://github.com/lidan1/PhotoSketchMAN
공식 코드High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks
https://github.com/ligaripash/KWtQ-face-alignment
공식 코드https://github.com/ligaripash/facecoresetnet
공식 코드FaceCoresetNet: Differentiable Coresets for Face Set Recognition
https://github.com/lightdxy/ict_deepfake
공식 코드Protecting Celebrities from DeepFake with Identity Consistency Transformer
https://github.com/lingxiao-he/Partial-Person-ReID
공식 코드https://github.com/liqi-casia/faceswapper
공식 코드Learning Disentangled Representation for One-shot Progressive Face Swapping
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.