Papers with Code 아카이브

3D Face Reconstruction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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/bunni90/facepastingattack

공식 코드

Face Pasting Attack

https://github.com/byangderek/CCF

공식 코드

Convolutional Channel Features

https://github.com/cabani/MaskedFace-Net

공식 코드

MaskedFace-Net -- A Dataset of Correctly/Incorrectly Masked Face Images in the Context of COVID-19

https://github.com/caltechvisionlab/frt-rapid-test

공식 코드

A Rapid Test for Accuracy and Bias of Face Recognition Technology

https://github.com/canpeng123/fscil_alice

공식 코드

Few-Shot Class-Incremental Learning from an Open-Set Perspective

https://github.com/carolineec/EverybodyDanceNow

공식 코드

Everybody Dance Now

https://github.com/cbsropenproject/6dof_face

공식 코드

Towards 3D Face Reconstruction in Perspective Projection: Estimating 6DoF Face Pose from Monocular Image

https://github.com/cc-hpc-itwm/facialgan

공식 코드

FacialGAN: Style Transfer and Attribute Manipulation on Synthetic Faces

https://github.com/cc13qq/sapd

공식 코드

Detecting Adversarial Faces Using Only Real Face Self-Perturbations

https://github.com/celebv-hq/celebv-hq

공식 코드

CelebV-HQ: A Large-Scale Video Facial Attributes Dataset

https://github.com/cgcl-codes/amt-gan

공식 코드

Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer

https://github.com/chailab-umich/ModelingIndividualEvaluators

공식 코드

The Whole Is Bigger Than the Sum of Its Parts: Modeling Individual Annotators to Capture Emotional Variability

https://github.com/chandlerbing65nm/FakeImageDetection

공식 코드

Frequency Masking for Universal Deepfake Detection

https://github.com/chaochao-lin/atr-fas

공식 코드

Enhancing Mobile Face Anti-Spoofing: A Robust Framework for Diverse Attack Types under Screen Flash

https://github.com/chaofengc/Face-Sketch

공식 코드

Face Sketch Synthesis with Style Transfer using Pyramid Column Feature

https://github.com/chaofengc/Face-Sketch-Wild

공식 코드

Semi-Supervised Learning for Face Sketch Synthesis in the Wild

https://github.com/charsyme/Human-Data-Generation-Framework

공식 코드

Efficient Realistic Data Generation Framework leveraging Deep Learning-based Human Digitization

https://github.com/chelsea234/hifi_ifdl

공식 코드

DeepFake-O-Meter v2.0: An Open Platform for DeepFake Detection

https://github.com/chelsea234/m2f2_det

공식 코드

Rethinking Vision-Language Model in Face Forensics: Multi-Modal Interpretable Forged Face Detector

https://github.com/chelsea234/multi-domain-learning-fas

공식 코드

Multi-domain Learning for Updating Face Anti-spoofing Models

https://github.com/chenchao666/Bone-Age-Assessment

공식 코드

Attention-Guided Discriminative Region Localization and Label Distribution Learning for Bone Age Assessment

https://github.com/chenqikong/m3fas

공식 코드

M3FAS: An Accurate and Robust MultiModal Mobile Face Anti-Spoofing System

https://github.com/chenzhe207/FDLSR

공식 코드

Fisher Discriminative Least Squares Regression for Image Classification

https://github.com/chihfanhsu/fl_detection

공식 코드

A Detailed Look At CNN-based Approaches In Facial Landmark Detection

https://github.com/choapinus/densenet10

공식 코드

On the Feasibility of Creating Iris Periocular Morphed Images

https://github.com/choyingw/SynergyNet

공식 코드

Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

https://github.com/choyingw/Voice2Mesh

공식 코드

Voice2Mesh: Cross-Modal 3D Face Model Generation from Voices

https://github.com/chrisdonahue/sdgan

공식 코드

Semantically Decomposing the Latent Spaces of Generative Adversarial Networks

https://github.com/christianbv/AgeNet

공식 코드

Facial Age Estimation using Convolutional Neural Networks

https://github.com/christophersims/fmri_adhd_classification

공식 코드

Highly Accurate FMRI ADHD Classification using time distributed multi modal 3D CNNs

https://github.com/chuangchuangtan/c2p-clip-deepfakedetection

공식 코드

C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detection

https://github.com/chuangchuangtan/data-independent-operator

공식 코드

Data-Independent Operator: A Training-Free Artifact Representation Extractor for Generalizable Deepfake Detection

https://github.com/chuangchuangtan/freqnet-deepfakedetection

공식 코드

Frequency-Aware Deepfake Detection: Improving Generalizability through Frequency Space Learning

https://github.com/chuangchuangtan/npr-deepfakedetection

공식 코드

Rethinking the Up-Sampling Operations in CNN-based Generative Network for Generalizable Deepfake Detection

https://github.com/clad23/clad

공식 코드

CLAD: Robust Audio Deepfake Detection Against Manipulation Attacks with Contrastive Learning

https://github.com/cleardusk/3DDFA

공식 코드

Face Alignment in Full Pose Range: A 3D Total Solution

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