Yaojie Liu

• PhD in Computer Science
• Research Scientist at Google Inc.

To defend against manipulation of image content, such as splicing, copy-move, and removal, we develop a Progressive Spatio-Channel Correlation Network (PSCC-Net) to detect and localize image manipulations. PSCC-Net processes the image in a two-path procedure: a top-down path that extracts local and global features and a bottom-up path that detects...

Prior studies show that the key to face anti-spoofing lies in the subtle image pattern, termed "spoof trace", e.g., color distortion, 3D mask edge, Moire pattern, and many others. Designing a generic face anti-spoofing model to estimate those spoof traces can improve not only the generalization of the spoof detection, but also the interpretability...

Prior studies show that the key to face anti-spoofing lies in the subtle image pattern, termed “spoof trace", e.g., color distortion, 3D mask edge, Moiré pattern, and many others. Designing a generic anti-spoofing model to estimate those spoof traces can improve both generalization and interpretability. Yet, this is a challenging task due to the di...

Prior studies show that the key to face anti-spoofing lies in the subtle image pattern, termed "spoof trace", e.g., color distortion, 3D mask edge, Moire pattern, and many others. Designing a generic anti-spoofing model to estimate those spoof traces can improve not only the generalization of the spoof detection, but also the interpretability of th...

Using printed photograph and replaying videos of biometric modalities, such as iris, fingerprint and face, are common attacks to fool the recognition systems for granting access as the genuine user. With the growing online person-to-person shopping (e.g., Ebay and Craigslist), such attacks also threaten those services, where the online photo illust...

Face is the most accessible biometric modality which can be used for identity verification in mobile phone applications, and it is vulnerable to many different presentation attacks, such as using a printed face/digital screen face to access the mobile phone. Presentation attack detection is a very critical step before feeding the face image to face...

Face anti-spoofing is designed to keep face recognition systems from recognizing fake faces as the genuine users. While advanced face anti-spoofing methods are developed, new types of spoof attacks are also being created and becoming a threat to all existing systems. We define the detection of unknown spoof attacks as Zero-Shot Face Anti-spoofing (...

Many prior face anti-spoofing works develop discriminative models for recognizing the subtle differences between live and spoof faces. Those approaches often regard the image as an indivisible unit, and process it holistically, without explicit modeling of the spoofing process. In this work, motivated by the noise modeling and denoising algorithms,...

Many prior face anti-spoofing works develop discriminative models for recognizing the subtle differences between live and spoof faces. Those approaches often regard the image as an indivisible unit, and process it holistically, without explicit modeling of the spoofing process. In this work, motivated by the noise modeling and denoising algorithms,...

Face anti-spoofing is the crucial step to prevent face recognition systems from a security breach. Previous deep learning approaches formulate face anti-spoofing as a binary classification problem. Many of them struggle to grasp adequate spoofing cues and generalize poorly. In this paper, we argue the importance of auxiliary supervision to guide th...

The face image is the most accessible biometric modality which is used for highly accurate face recognition systems, while it is vulnerable to many different types of presentation attacks. Face anti-spoofing is a very critical step before feeding the face image to biometric systems. In this paper , we propose a novel two-stream CNN-based approach f...

Face alignment is a classic problem in the computer vision field. Previous works mostly focus on sparse alignment with a limited number of facial landmark points, i.e., facial landmark detection. In this paper, for the first time, we aim at providing a very dense 3D alignment for large-pose face images. To achieve this, we train a CNN to estimate t...

Many face recognition applications require a precise 3D reconstruction of the shape of the face, even when only a single 2D image is available. We present a novel regression approach that learns to detect facial landmark points and estimate their 3D shape rapidly and accurately from a single face image. The main idea is to regress a function f(.) t...

Image inpainting is an important research topic in the field of image processing. The objective of inpainting is to 'guess' the lost information according to surrounding image information, which can be applied in old photo restoration, object removal and demosaicing. Based on the foundation of previous literature of image inpainting and image model...