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3D Face Reconstruction

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하위 태스크: 1
평가표: 9
보존된 평가 기록: 94

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/qiqitao77/awesome-comprehensive-deepfake-detection

공식 코드

Evolving from Single-modal to Multi-modal Facial Deepfake Detection: A Survey

https://github.com/qiqitao77/comprehensive-advances-in-deepfake-detection-spanning-diverse-modalities

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Evolving from Single-modal to Multi-modal Facial Deepfake Detection: A Survey

https://github.com/qizhangli/nobox-attacks

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Practical No-box Adversarial Attacks against DNNs

https://github.com/quarxilon/generator_attribution

공식 코드

Transferable Class-Modelling for Decentralized Source Attribution of GAN-Generated Images

https://github.com/quereste/implicit-deepfake

공식 코드

Deepfake for the Good: Generating Avatars through Face-Swapping with Implicit Deepfake Generation

https://github.com/radekd91/emoca

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EMOCA: Emotion Driven Monocular Face Capture and Animation

https://github.com/radu-dogaru/LB-CNN-compact-and-fast-binary-including-very-fast-ELM

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LB-CNN: An Open Source Framework for Fast Training of Light Binary Convolutional Neural Networks using Chainer and Cupy

https://github.com/rafaelmmamede/fairness_ocfr

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Fairness Under Cover: Evaluating the Impact of Occlusions on Demographic Bias in Facial Recognition

https://github.com/rafaelvareto/maximal-entropy-loss

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Open-set Face Recognition with Neural Ensemble, Maximal Entropy Loss and Feature Augmentation

https://github.com/raining-dev/avt2-dwf

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AVT2-DWF: Improving Deepfake Detection with Audio-Visual Fusion and Dynamic Weighting Strategies

https://github.com/rainy-xu/tall4deepfake

공식 코드

TALL: Thumbnail Layout for Deepfake Video Detection

https://github.com/rama0126/pwtf-dvd

공식 코드

Beyond Spatial Frequency: Pixel-wise Temporal Frequency-based Deepfake Video Detection

https://github.com/ramihaf/mtf_data_set

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Multi-Task Faces (MTF) Data Set: A Legally and Ethically Compliant Collection of Face Images for Various Classification Tasks

https://github.com/raphaelmemmesheimer/sl-dml

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SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition

https://github.com/raywang335/l2rclip

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Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal Classification

https://github.com/razla/xai-based-detection-of-adversarial-attacks-on-deepfake-detectors

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XAI-Based Detection of Adversarial Attacks on Deepfake Detectors

https://github.com/realityengines/post_hoc_debiasing

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Intra-Processing Methods for Debiasing Neural Networks

https://github.com/recluzegeek/AWARE-NET

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AWARE-NET: Adaptive Weighted Averaging for Robust Ensemble Network in Deepfake Detection

https://github.com/redcping/Delta_Age_AdaIN

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DAA: A Delta Age AdaIN operation for age estimation via binary code transformer

https://github.com/renderme-360/renderme-360

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RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars

https://github.com/renmin1991/perturbation-inactivate

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Perturbation Inactivation Based Adversarial Defense for Face Recognition

https://github.com/rgb91/temporal-deepfake-segmentation

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Undercover Deepfakes: Detecting Fake Segments in Videos

https://github.com/riaduli/thresholded_event_vision_face_dataset

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Descriptor: Face Detection Dataset for Programmable Threshold-Based Sparse-Vision

https://github.com/ristea/xmad-bench

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XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark

https://github.com/rizhaocai/metapattern_fas

공식 코드

Learning Meta Pattern for Face Anti-Spoofing

https://github.com/rlit/LatentRANSAC

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https://github.com/rmushfiqur2/deepfake_op_rel

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Individualized Deepfake Detection Exploiting Traces Due to Double Neural-Network Operations

https://github.com/rohdelab/drcdt_face

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Local Sliced-Wasserstein Feature Sets for Illumination-invariant Face Recognition

https://github.com/rohit7044/3D-GANTex

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3D-GANTex: 3D Face Reconstruction with StyleGAN3-based Multi-View Images and 3DDFA based Mesh Generation

https://github.com/ronny3050/PrimateFaceRecognition

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Face Recognition: Primates in the Wild

https://github.com/roscibely/Gender-Classification

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Predicting Gender by First Name Using Character-level Machine Learning

https://github.com/royorel/FFHQ-Aging-Dataset

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Lifespan Age Transformation Synthesis

https://github.com/royorel/Lifespan_Age_Transformation_Synthesis

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Lifespan Age Transformation Synthesis

https://github.com/royorel/StyleSDF

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StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation

https://github.com/rperi/trustworthy-asv-fairness

공식 코드

To train or not to train adversarially: A study of bias mitigation strategies for speaker recognition

https://github.com/rshaojimmy/AAAI2020-RFMetaFAS

공식 코드

Regularized Fine-grained Meta Face Anti-spoofing

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.