Papers with Code 아카이브
Facial Recognition and Modelling
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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/talreiss/factor
공식 코드https://github.com/tamlhp/dfd_benchmark
공식 코드A War Beyond Deepfake: Benchmarking Facial Counterfeits and Countermeasures
https://github.com/taowangzj/llformer
공식 코드Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method
https://github.com/tarun360/speakerprofiling
공식 코드Estimation of speaker age and height from speech signal using bi-encoder transformer mixture model
https://github.com/tavihalperin/AV-sync
공식 코드https://github.com/taylor-xy0827/Ada-DF
공식 코드Ada-DF: An Adaptive Label Distribution Fusion Network For Facial Expression Recognition
https://github.com/taylover-pei/SSDG-CVPR2020
공식 코드https://github.com/tesfayz/ccm_madrl_mec
공식 코드https://github.com/teslatasy/popos
공식 코드https://github.com/tfwu/FaceDetection-ConvNet-3D
공식 코드Face Detection with End-to-End Integration of a ConvNet and a 3D Model
https://github.com/thended32/analyzingcombineddegradations
공식 코드Analyzing the Effect of Combined Degradations on Face Recognition
https://github.com/thesouthfrog/stylealign
공식 코드Aggregation via Separation: Boosting Facial Landmark Detector with Semi-Supervised Style Translation
https://github.com/thetna/medical_image_segmentation
공식 코드https://github.com/thiagoambiel/PortraitStylization
공식 코드Portrait Stylization: Artistic Style Transfer with Auxiliary Networks for Human Face Stylization
https://github.com/thinkercache/stylegan2-ada-pytorch
공식 코드High Fidelity Synthetic Face Generation for Rosacea Skin Condition from Limited Data
https://github.com/thomas-wyh/fuseanypart
공식 코드FuseAnyPart: Diffusion-Driven Facial Parts Swapping via Multiple Reference Images
https://github.com/thorbenortmann/emohevrdb-sfer
공식 코드https://github.com/thorbenortmann/emoji-hero-vr-database
공식 코드https://github.com/thu-huangzc/FFAA
공식 코드FFAA: Multimodal Large Language Model based Explainable Open-World Face Forgery Analysis Assistant
https://github.com/thu-ml/at3d
공식 코드Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition
https://github.com/thu-ml/attack-bard
공식 코드https://github.com/tiandunx/FFC
공식 코드An Efficient Training Approach for Very Large Scale Face Recognition
https://github.com/tiandunx/loss_function_search
공식 코드https://github.com/tingfengx/Emoji-Expression-Mask.PyTorch
공식 코드Real-Time Facial Expression Emoji Masking with Convolutional Neural Networks and Homography
https://github.com/tinkoff-ai/probabilistic-embeddings
공식 코드https://github.com/tizfa/tweepfake_deepfake_text_detection
공식 코드https://github.com/tkarras/progressive_growing_of_gans
공식 코드Progressive Growing of GANs for Improved Quality, Stability, and Variation
https://github.com/tldrafael/facereconstructionwithvaeandfacemasks
공식 코드Face Reconstruction with Variational Autoencoder and Face Masks
https://github.com/tobuta/PolyGlotFake
공식 코드PolyGlotFake: A Novel Multilingual and Multimodal DeepFake Dataset
https://github.com/tokaka22/gmaa
공식 코드https://github.com/tomlimi/MT-Tokenizer-Bias
공식 코드https://github.com/tongzhou0101/bileve-official
공식 코드Bileve: Securing Text Provenance in Large Language Models Against Spoofing with Bi-level Signature
https://github.com/tpulkit/txt2vid
공식 코드Txt2Vid: Ultra-Low Bitrate Compression of Talking-Head Videos via Text
https://github.com/tranluan/Nonlinear_Face_3DMM
공식 코드https://github.com/truongvu2000nd/afs
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.