3D Face Modelling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/bieltura/Automotive_face_detector
공식 코드Low cost enhanced security face recognition with stereo cameras
https://github.com/billyxyb/facednerf
공식 코드FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models
https://github.com/billyxyb/fdnerf
공식 코드FaceDNeRF: Semantics-Driven Face Reconstruction, Prompt Editing and Relighting with Diffusion Models
https://github.com/bilylee/DCQ
공식 코드Dynamic Class Queue for Large Scale Face Recognition In the Wild
https://github.com/bing-li-ai/AniGAN
공식 코드AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation
https://github.com/bintsi/adaptive-graph-learning
공식 코드Multimodal brain age estimation using interpretable adaptive population-graph learning
https://github.com/bintsi/brain-age-population-graphs
공식 코드https://github.com/biomedia-mbzuai/fetalclip
공식 코드FetalCLIP: A Visual-Language Foundation Model for Fetal Ultrasound Image Analysis
https://github.com/birdwcp/qcs
공식 코드QCS: Feature Refining from Quadruplet Cross Similarity for Facial Expression Recognition
https://github.com/bit-ml/DeCLIP
공식 코드DeCLIP: Decoding CLIP representations for deepfake localization
https://github.com/bit-ml/avh-align
공식 코드Circumventing shortcuts in audio-visual deepfake detection datasets with unsupervised learning
https://github.com/bit-ml/dolos
공식 코드Weakly-supervised deepfake localization in diffusion-generated images
https://github.com/bita-github/MRP-FER
공식 코드https://github.com/bj80heyue/Learning_One_Shot_Face_Reenactment
공식 코드https://github.com/bjzhb666/GS-LoRA
공식 코드https://github.com/bluecontra/AAAI2021-VDFP
공식 코드Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction
https://github.com/bmazoure/sparseMuJoCo
공식 코드Leveraging exploration in off-policy algorithms via normalizing flows
https://github.com/bobetocalo/bobetocalo_pami20
공식 코드https://github.com/bodhis4ttva/lhc_net
공식 코드Local Multi-Head Channel Self-Attention for Facial Expression Recognition
https://github.com/bok-bok/MSOC
공식 코드A Multi-Stream Fusion Approach with One-Class Learning for Audio-Visual Deepfake Detection
https://github.com/borrisonxiao/icefall
공식 코드HK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech Translation
https://github.com/boschresearch/DD_OPG
공식 코드https://github.com/boschresearch/dist-mbrl
공식 코드https://github.com/boschresearch/ube-mbrl
공식 코드https://github.com/boutiquelee/deepfakeempiricalstudy
공식 코드How Generalizable are Deepfake Image Detectors? An Empirical Study
https://github.com/bovifocr/tcdiff
공식 코드TCDiff: Triple Condition Diffusion Model with 3D Constraints for Stylizing Synthetic Faces
https://github.com/bplank/bleaching-text
공식 코드Bleaching Text: Abstract Features for Cross-lingual Gender Prediction
https://github.com/brain-age/otfpf
공식 코드https://github.com/brkljac/videoface2.0
공식 코드https://github.com/browatbn2/3FabRec
공식 코드https://github.com/bsi-ofiq/ofiq-project
공식 코드Deep Learning-based Compression Detection for explainable Face Image Quality Assessment
https://github.com/bunni90/facepastingattack
공식 코드https://github.com/byangderek/CCF
공식 코드https://github.com/cabani/MaskedFace-Net
공식 코드MaskedFace-Net -- A Dataset of Correctly/Incorrectly Masked Face Images in the Context of COVID-19
https://github.com/caelan/SS-Replan
공식 코드Online Replanning in Belief Space for Partially Observable Task and Motion Problems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.