https://github.com/envision-research/gpt4affectivity
공식 코드GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing
Papers with Code 아카이브
3D Face Reconstruction
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3D Face Reconstruction is a computer vision task that involves creating a 3D model of a human face from a 2D image or a set of images. The goal of 3D face reconstruction is to reconstruct a digital 3D representation of a person's face, which can be used for various applications such as animation, virtual reality, and biometric identification.
<span style="color:grey; opacity: 0.6">( Image credit: 3DDFA_V2 )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ergastialex/ldm-diffusion-sem
공식 코드Controllable Face Synthesis with Semantic Latent Diffusion Models
https://github.com/ergastialex/sca-dm
공식 코드Controllable Face Synthesis with Semantic Latent Diffusion Models
https://github.com/erprogs/CViT
공식 코드Deepfake Video Detection Using Convolutional Vision Transformer
https://github.com/erprogs/genconvit
공식 코드Deepfake Video Detection Using Generative Convolutional Vision Transformer
https://github.com/eth-sri/synthpai
공식 코드https://github.com/eurecom-asp/malafide
공식 코드https://github.com/eurecom-asp/pc-darts-anti-spoofing
공식 코드Partially-Connected Differentiable Architecture Search for Deepfake and Spoofing Detection
https://github.com/eurecom-asp/raw-pc-darts-anti-spoofing
공식 코드Raw Differentiable Architecture Search for Speech Deepfake and Spoofing Detection
https://github.com/eurecom-asp/rawgat-st-antispoofing
공식 코드https://github.com/eurecom-fscv/2d-malafide
공식 코드2D-Malafide: Adversarial Attacks Against Face Deepfake Detection Systems
https://github.com/eye-tracking-for-physiological-sensing/eyelorin
공식 코드https://github.com/face3d0725/FaceExtraction
공식 코드FaceOcc: A Diverse, High-quality Face Occlusion Dataset for Human Face Extraction
https://github.com/face3d0725/face_de_mask
공식 코드https://github.com/facebookresearch/KeypointNeRF
공식 코드https://github.com/facebookresearch/detectron
공식 코드https://github.com/fahadshamshad/clip2protect
공식 코드CLIP2Protect: Protecting Facial Privacy using Text-Guided Makeup via Adversarial Latent Search
https://github.com/fahadshamshad/deep-facial-privacy-prior
공식 코드Makeup-Guided Facial Privacy Protection via Untrained Neural Network Priors
https://github.com/fairdeface/FairDeface
공식 코드FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation Methods
https://github.com/fangyini/rmes
공식 코드RMES: Real-Time Micro-Expression Spotting Using Phase From Riesz Pyramid
https://github.com/faniamokhayeri/C-GAN
공식 코드https://github.com/faniamokhayeri/DSFS
공식 코드Domain-Specific Face Synthesis for Video Face Recognition from a Single Sample Per Person
https://github.com/farzad-bz/harmonizing-flows
공식 코드Harmonizing Flows: Leveraging normalizing flows for unsupervised and source-free MRI harmonization
https://github.com/fatemejamalii/e2f-net
공식 코드https://github.com/faysal-md/unmasking-deepfake-faces-from-videos-an-explainable-cost-sensitive-deep-learning-approach-ieee2023
공식 코드Unmasking Deepfake Faces from Videos Using An Explainable Cost-Sensitive Deep Learning Approach
https://github.com/fbiying87/demographic-bias-visualization
공식 코드Towards Explaining Demographic Bias through the Eyes of Face Recognition Models
https://github.com/fbiying87/explainable_fiqa_with_amva
공식 코드https://github.com/fdbtrs/AdaDistill
공식 코드AdaDistill: Adaptive Knowledge Distillation for Deep Face Recognition
https://github.com/fdbtrs/ElasticFace
공식 코드https://github.com/fdbtrs/IDiff-Face
공식 코드IDiff-Face: Synthetic-based Face Recognition through Fizzy Identity-Conditioned Diffusion Models
https://github.com/fdbtrs/QuantFace
공식 코드QuantFace: Towards Lightweight Face Recognition by Synthetic Data Low-bit Quantization
https://github.com/fdbtrs/Self-restrained-Triplet-Loss
공식 코드Self-restrained Triplet Loss for Accurate Masked Face Recognition
https://github.com/fdbtrs/Unsupervised-Face-Recognition-using-Unlabeled-Synthetic-Data
공식 코드Unsupervised Face Recognition using Unlabeled Synthetic Data
https://github.com/fdbtrs/cr-fiqa
공식 코드CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability
https://github.com/fdbtrs/exfacegan
공식 코드https://github.com/fdbtrs/masked-face-recognition-kd
공식 코드Mask-invariant Face Recognition through Template-level Knowledge Distillation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.