Search Results for author:
Found 11 papers, 3 papers with code
Robust Egocentric Photo-realistic Facial Expression Transfer for Virtual Reality
Social presence, the feeling of being there with a real person, will fuel the next generation of communication systems driven by digital humans in virtual reality (VR).
Noise Modeling, Synthesis and Classification for Generic Object Anti-Spoofing
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.
Deep Tree Learning for Zero-shot Face Anti-Spoofing
We define the detection of unknown spoof attacks as Zero-Shot Face Anti-spoofing (ZSFA).
Face De-Spoofing: Anti-Spoofing via Noise Modeling
In this work, motivated by the noise modeling and denoising algorithms, we identify a new problem of face de-spoofing, for the purpose of anti-spoofing: inversely decomposing a spoof face into a spoof noise and a live face, and then utilizing the spoof noise for classification.
Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision
Face anti-spoofing is the crucial step to prevent face recognition systems from a security breach.
Do Convolutional Neural Networks Learn Class Hierarchy?
We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data.
Dense Face Alignment
Face alignment is a classic problem in the computer vision field.
Ranked #2 on
Face Alignment
on AFLW-LFPA
Pose-Invariant Face Alignment with a Single CNN
Face alignment has witnessed substantial progress in the last decade.
Ranked #12 on
Facial Landmark Detection
on 300W
Large-Pose Face Alignment via CNN-Based Dense 3D Model Fitting
Large-pose face alignment is a very challenging problem in computer vision, which is used as a prerequisite for many important vision tasks, e. g, face recognition and 3D face reconstruction.
Pose-Invariant 3D Face Alignment
Face alignment aims to estimate the locations of a set of landmarks for a given image.
A Bayesian Framework for Sparse Representation-Based 3D Human Pose Estimation
Our Bayesian framework estimates a posterior distribution for the sparse codes and the dictionaries from labeled training data.
