https://github.com/magnet300/camme
공식 코드CAMME: Adaptive Deepfake Image Detection with Multi-Modal Cross-Attention
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
CAMME: Adaptive Deepfake Image Detection with Multi-Modal Cross-Attention
A General Framework for Adversarial Examples with Objectives
PROVES: Establishing Image Provenance using Semantic Signatures
Attributes Shape the Embedding Space of Face Recognition Models
Face Super-Resolution Using Stochastic Differential Equations
Efficient Explainable Face Verification based on Similarity Score Argument Backpropagation
Tackling Face Verification Edge Cases: In-Depth Analysis and Human-Machine Fusion Approach
Octuplet Loss: Make Face Recognition Robust to Image Resolution
Explainable Model-Agnostic Similarity and Confidence in Face Verification
Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation
Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowds
Reveal to Revise: An Explainable AI Life Cycle for Iterative Bias Correction of Deep Models
UDC-VIT: A Real-World Video Dataset for Under-Display Cameras
Face Hallucination via Split-Attention in Split-Attention Network
Perceptual Conversational Head Generation with Regularized Driver and Enhanced Renderer
Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization
Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
Nasal Patches and Curves for Expression-robust 3D Face Recognition
Unsupervised Face Morphing Attack Detection via Self-paced Anomaly Detection
SynthASpoof: Developing Face Presentation Attack Detection Based on Privacy-friendly Synthetic Data
Towards Identity-Aware Cross-Modal Retrieval: a Dataset and a Baseline
MetaFBP: Learning to Learn High-Order Predictor for Personalized Facial Beauty Prediction
Single camera pose estimation using Bayesian filtering and Kinect motion priors
Multi-spectral Class Center Network for Face Manipulation Detection and Localization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.