https://github.com/aimagelab/COCOFake
공식 코드Parents and Children: Distinguishing Multimodal DeepFakes from Natural Images
Papers with Code 아카이브
Face Reconstruction
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Face reconstruction is the task of recovering the facial geometry of a face from an image.
<span style="color:grey; opacity: 0.6">( Image credit: Microsoft Deep3DFaceReconstruction )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/aimagelab/code
공식 코드Contrasting Deepfakes Diffusion via Contrastive Learning and Global-Local Similarities
https://github.com/aimultimedialab/favci2d-face-verification-with-challenging-imposters-and-diversified-demographics
공식 코드Face Verification with Challenging Imposters and Diversified Demographics
https://github.com/ajev-research/agg-layers-deepfake-detection
공식 코드https://github.com/albertpumarola/GANimation
공식 코드GANimation: Anatomically-aware Facial Animation from a Single Image
https://github.com/ali-vilab/dreamtalk
공식 코드DreamTalk: When Emotional Talking Head Generation Meets Diffusion Probabilistic Models
https://github.com/alibaba-miil/headsharingkd
공식 코드It's All in the Head: Representation Knowledge Distillation through Classifier Sharing
https://github.com/alinlab/BAR
공식 코드Learning from Failure: Training Debiased Classifier from Biased Classifier
https://github.com/aliprf/ASMNet
공식 코드ASMNet: a Lightweight Deep Neural Network for Face Alignment and Pose Estimation
https://github.com/aliprf/acr-loss
공식 코드ACR Loss: Adaptive Coordinate-based Regression Loss for Face Alignment
https://github.com/aliprf/ganalyzer
공식 코드GANalyzer: Analysis and Manipulation of GANs Latent Space for Controllable Face Synthesis
https://github.com/aliprf/kd-loss
공식 코드Facial Landmark Points Detection Using Knowledge Distillation-Based Neural Networks
https://github.com/alldbi/FLM
공식 코드https://github.com/alonzolfi/adversarialmask
공식 코드Adversarial Mask: Real-World Universal Adversarial Attack on Face Recognition Model
https://github.com/altndrr/clup
공식 코드Cluster-level pseudo-labelling for source-free cross-domain facial expression recognition
https://github.com/amazon-research/gendered-profession-translations
공식 코드Faithful Target Attribute Prediction in Neural Machine Translation
https://github.com/amilkh/cs230-fer
공식 코드https://github.com/aminesi/robustness-on-device
공식 코드Robustness Analysis of Deep Learning Frameworks on Mobile Platforms
https://github.com/amoonfana/fastface
공식 코드FastFace: Fast-converging Scheduler for Large-scale Face Recognition Training with One GPU
https://github.com/andrekassis/DiffBreak
공식 코드https://github.com/andrekassis/ai-watermark
공식 코드UnMarker: A Universal Attack on Defensive Image Watermarking
https://github.com/andresprados/spiga
공식 코드Shape Preserving Facial Landmarks with Graph Attention Networks
https://github.com/angelomenezes/Pytorch_Face_SR
공식 코드https://github.com/anger-man/unsupervised-depth-estimation
공식 코드Unsupervised Single-shot Depth Estimation using Perceptual Reconstruction
https://github.com/anguyen8/deepface-emd
공식 코드https://github.com/anguyen8/face-vit
공식 코드Fast and Interpretable Face Identification for Out-Of-Distribution Data Using Vision Transformers
https://github.com/anhttran/extreme_3d_faces
공식 코드https://github.com/anjith2006/bob.paper.cross_modal_focal_loss_cvpr2021
공식 코드https://github.com/anjith2006/bob.paper.deep_pix_bis_pad.icb2019
공식 코드Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection
https://github.com/anjith2006/bob.paper.ijcb2021_vision_transformer_pad
공식 코드On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing
https://github.com/anmol2059/svdd2024
공식 코드https://github.com/anonrep/iba-for-video-sequences
공식 코드Extending Information Bottleneck Attribution to Video Sequences
https://github.com/anonymous-author-sub/seeable
공식 코드SeeABLE: Soft Discrepancies and Bounded Contrastive Learning for Exposing Deepfakes
https://github.com/anonymoususera/ava
공식 코드AVA: Inconspicuous Attribute Variation-based Adversarial Attack bypassing DeepFake Detection
https://github.com/antonibigata/Laughing-Matters
공식 코드Laughing Matters: Introducing Laughing-Face Generation using Diffusion Models
https://github.com/anubhav1997/youneednodataset
공식 코드A Dataless FaceSwap Detection Approach Using Synthetic Images
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.