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/shaibagon/large_scale_cc

공식 코드

Large Scale Correlation Clustering Optimization

https://github.com/shanface33/deepfake_model_attribution

공식 코드

Model Attribution of Face-swap Deepfake Videos

https://github.com/shanface33/gpt4mf_ub

공식 코드

Can ChatGPT Detect DeepFakes? A Study of Using Multimodal Large Language Models for Media Forensics

https://github.com/shangeth/Speaker-Representation-for-Speaker-Profiling

공식 코드

Learning Speaker Representation with Semi-supervised Learning approach for Speaker Profiling

https://github.com/sharpstill/AU_R-CNN

공식 코드

AU R-CNN: Encoding Expert Prior Knowledge into R-CNN for Action Unit Detection

https://github.com/shawnxyang/tip-im

공식 코드

Towards Face Encryption by Generating Adversarial Identity Masks

https://github.com/shengfly/global-local-transformer

공식 코드

Global-Local Transformer for Brain Age Estimation

https://github.com/sherrycattt/REGDet

공식 코드

Recurrent Exposure Generation for Low-Light Face Detection

https://github.com/shighghyujie/newpatch-rl

공식 코드

Simultaneously Optimizing Perturbations and Positions for Black-box Adversarial Patch Attacks

https://github.com/shiluo1990/SFA

공식 코드

SFA: Small Faces Attention Face Detector

https://github.com/shiluo1990/bdc

공식 코드

Bounding-box deep calibration for high performance face detection

https://github.com/shimmer-ghq/deepfidelity

공식 코드

DeepFidelity: Perceptual Forgery Fidelity Assessment for Deepfake Detection

https://github.com/shrezaei/Target-Agnostic-Attack

공식 코드

A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning

https://github.com/shuchaoduan/qafe-net

공식 코드

QAFE-Net: Quality Assessment of Facial Expressions with Landmark Heatmaps

https://github.com/shuvenduroy/activefer

공식 코드

Active Learning with Contrastive Pre-training for Facial Expression Recognition

https://github.com/shuvenduroy/ssl_fer

공식 코드

Analysis of Semi-Supervised Methods for Facial Expression Recognition

https://github.com/shuvenduroy/ssl_fer_ood

공식 코드

Exploring the Boundaries of Semi-Supervised Facial Expression Recognition using In-Distribution, Out-of-Distribution, and Unconstrained Data

https://github.com/siddiquelatif/URDU-Dataset

공식 코드

Cross Lingual Speech Emotion Recognition: Urdu vs. Western Languages

https://github.com/silence-tang/artnerf

공식 코드

ArtNeRF: A Stylized Neural Field for 3D-Aware Cartoonized Face Synthesis

https://github.com/silvialaurapintea/reg-cls

공식 코드

A step towards understanding why classification helps regression

https://github.com/skjack/diffusionfake

공식 코드

DiffusionFake: Enhancing Generalization in Deepfake Detection via Guided Stable Diffusion

https://github.com/skrantidatta/lipinc

공식 코드

Exposing Lip-syncing Deepfakes from Mouth Inconsistencies

https://github.com/skrantidatta/lipinc-v2

공식 코드

Detecting Lip-Syncing Deepfakes: Vision Temporal Transformer for Analyzing Mouth Inconsistencies

https://github.com/skylar-sutherland/single-scan-3dmms

공식 코드

Building 3D Morphable Models from a Single Scan

https://github.com/slundberg/shap

공식 코드

Explaining deep learning models for spoofing and deepfake detection with SHapley Additive exPlanations

https://github.com/smile-ffg/he-man-concrete

공식 코드

HE-MAN -- Homomorphically Encrypted MAchine learning with oNnx models

https://github.com/smuelpeng/sgps-noisefreedml

공식 코드

Enhancing Sample Utilization in Noise-Robust Deep Metric Learning With Subgroup-Based Positive-Pair Selection

https://github.com/socialabubi/iFakeFaceDB

공식 코드

GANprintR: Improved Fakes and Evaluation of the State of the Art in Face Manipulation Detection

https://github.com/sohailahmedkhan/CLIPping-the-Deception

공식 코드

CLIPping the Deception: Adapting Vision-Language Models for Universal Deepfake Detection

https://github.com/soheilb/multimodal_dictionary_learning

공식 코드

Multimodal Task-Driven Dictionary Learning for Image Classification

https://github.com/somuchtome/faceswap

공식 코드

Face Swap via Diffusion Model

https://github.com/songluchuan/adasr-talkinghead

공식 코드

Adaptive Super Resolution For One-Shot Talking-Head Generation

https://github.com/sowmen/face-cutout

공식 코드

Towards Solving the DeepFake Problem : An Analysis on Improving DeepFake Detection using Dynamic Face Augmentation

https://github.com/sowwnn/KFusion-Dual-Domain-for-Speech-to-Landmarks

공식 코드

KAN-Based Fusion of Dual-Domain for Audio-Driven Facial Landmarks Generation

https://github.com/spaghettisystems/emotion_whisper

공식 코드

Towards Generalizable SER: Soft Labeling and Data Augmentation for Modeling Temporal Emotion Shifts in Large-Scale Multilingual Speech

https://github.com/spring-epfl/iccwd

공식 코드

A Manually Annotated Image-Caption Dataset for Detecting Children in the Wild

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