https://github.com/louisbearing/hmo-audio
공식 코드A Comprehensive Multi-scale Approach for Speech and Dynamics Synchrony in Talking Head Generation
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/louisbearing/unconditionalheadmotion
공식 코드Autoregressive GAN for Semantic Unconditional Head Motion Generation
https://github.com/lovesiamesecat/favit
공식 코드Generalized Face Forgery Detection via Adaptive Learning for Pre-trained Vision Transformer
https://github.com/lsibabnikz/ai-kd
공식 코드AI-KD: Towards Alignment Invariant Face Image Quality Assessment Using Knowledge Distillation
https://github.com/lsibabnikz/faceqan
공식 코드FaceQAN: Face Image Quality Assessment Through Adversarial Noise Exploration
https://github.com/lsibabnikz/optimization-based-improvement-of-fiqa-techniques
공식 코드Optimization-Based Improvement of Face Image Quality Assessment Techniques
https://github.com/lsy0882/FakeMix
공식 코드WWW: Where, Which and Whatever Enhancing Interpretability in Multimodal Deepfake Detection
https://github.com/ltrottier/deep-collaboration-network
공식 코드Multi-Task Learning by Deep Collaboration and Application in Facial Landmark Detection
https://github.com/lucasxlu/TransFBP
공식 코드Transferring Rich Deep Features for Facial Beauty Prediction
https://github.com/luisrui/seeing-ai-system
공식 코드https://github.com/lukasstruppek/class_attribute_inference_attacks
공식 코드https://github.com/lukecq1231/generalized-pooling
공식 코드https://github.com/lupaopao/gpt4affectivity
공식 코드GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing
https://github.com/luxiangju-PersonAI/iCartoonFace
공식 코드https://github.com/lwkjjonak/quantum_neural_network_classifiers
공식 코드https://github.com/lxq1000/dfa-instruct
공식 코드https://github.com/lxq1000/faceptor
공식 코드https://github.com/lxq1000/swinface
공식 코드https://github.com/lyp-deeplearning/mos-multi-task-face-detect
공식 코드https://github.com/machine-listeners-valencia/fsl_osr_dataset_baseline
공식 코드https://github.com/magnet300/camme
공식 코드CAMME: Adaptive Deepfake Image Detection with Multi-Modal Cross-Attention
https://github.com/mahdi-darvish/gans-augmented-pet-classifier
공식 코드https://github.com/mahehu/TUT-live-age-estimator
공식 코드https://github.com/mahmoods01/agns
공식 코드A General Framework for Adversarial Examples with Objectives
https://github.com/manavkulshrestha/imgprov
공식 코드PROVES: Establishing Image Provenance using Semantic Signatures
https://github.com/mantonios107/attrs-fr-embs
공식 코드Attributes Shape the Embedding Space of Face Recognition Models
https://github.com/manyilee/plada
공식 코드https://github.com/mapooon/blendface
공식 코드https://github.com/marcelowds/sr-sde
공식 코드Face Super-Resolution Using Stochastic Differential Equations
https://github.com/marcohuber/xssab
공식 코드Efficient Explainable Face Verification based on Similarity Score Argument Backpropagation
https://github.com/mariusarvinte/robust-face-verification
공식 코드https://github.com/martlgap/human-machine-fusion
공식 코드Tackling Face Verification Edge Cases: In-Depth Analysis and Human-Machine Fusion Approach
https://github.com/martlgap/octuplet-loss
공식 코드Octuplet Loss: Make Face Recognition Robust to Image Resolution
https://github.com/martlgap/x-face-verification
공식 코드Explainable Model-Agnostic Similarity and Confidence in Face Verification
https://github.com/matteoferrara/morphing-attack-potential
공식 코드https://github.com/mattgroh/cognitive-science-detecting-deepfakes
공식 코드Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowds
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.