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/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/lustoo/fghv
공식 코드Feature Generation and Hypothesis Verification for Reliable Face Anti-Spoofing
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
https://github.com/maxdreyer/reveal2revise
공식 코드Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models
https://github.com/mcrl/udc-sit
공식 코드UDC-VIT: A Real-World Video Dataset for Under-Display Cameras
https://github.com/mdhosen/mask-face-inpainting-using-residual-attention-unet
공식 코드https://github.com/mdswyz/SISN-Face-Hallucination
공식 코드Face Hallucination via Split-Attention in Split-Attention Network
https://github.com/megvii-research/MM2022-ViCoPerceptualHeadGeneration
공식 코드Perceptual Conversational Head Generation with Regularized Driver and Enhanced Renderer
https://github.com/megvii-research/caddm
공식 코드Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization
https://github.com/megvii-research/fst-matching
공식 코드https://github.com/mehrdadsaberi/watermark_robustness
공식 코드Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.