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Found 15 papers, 4 papers with code
Heterogeneous Face Recognition via Face Synthesis with Identity-Attribute Disentanglement
Secondly, we devise a face synthesis module (FSM) to generate a large number of images with stochastic combinations of disentangled identities and attributes for enriching the attribute diversity of synthetic images.
Rethinking Image Cropping: Exploring Diverse Compositions From Global Views
In this paper, we regard image cropping as a set prediction problem.
Causal Representation Learning for Context-Aware Face Transfer
Human face synthesis involves transferring knowledge about the identity and identity-dependent face shape (IDFS) of a human face to target face images where the context (e. g., facial expressions, head poses, and other background factors) may change dramatically.
Pareidolia Face Reenactment
We present a new application direction named Pareidolia Face Reenactment, which is defined as animating a static illusory face to move in tandem with a human face in the video.
Information Bottleneck Disentanglement for Identity Swapping
In this work, we propose a novel information disentangling and swapping network, called InfoSwap, to extract the most expressive information for identity representation from a pre-trained face recognition model.
Everything's Talkin': Pareidolia Face Reenactment
We present a new application direction named Pareidolia Face Reenactment, which is defined as animating a static illusory face to move in tandem with a human face in the video.
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-Identification
Visible-Infrared person re-identification (VI-ReID) aims to match cross-modality pedestrian images, breaking through the limitation of single-modality person ReID in dark environment.
AOT: Appearance Optimal Transport Based Identity Swapping for Forgery Detection
However, due to the lack of Deepfakes datasets with large variance in appearance, which can be hardly produced by recent identity swapping methods, the detection algorithm may fail in this situation.
DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition
As a consequence, massive new diverse paired heterogeneous images with the same identity can be generated from noises.
Deep Momentum Uncertainty Hashing
It embodies the uncertainty of the hashing network to the corresponding input image.
Dual Variational Generation for Low Shot Heterogeneous Face Recognition
Specifically, we first introduce a dual variational autoencoder to represent a joint distribution of paired heterogeneous images.
Cross-Spectral Face Hallucination via Disentangling Independent Factors
The cross-sensor gap is one of the challenges that have aroused much research interests in Heterogeneous Face Recognition (HFR).
High Fidelity Face Manipulation with Extreme Poses and Expressions
Furthermore, due to the lack of high-resolution face manipulation databases to verify the effectiveness of our method, we collect a new high-quality Multi-View Face (MVF-HQ) database.
Dual Variational Generation for Low-Shot Heterogeneous Face Recognition
Then, in order to ensure the identity consistency of the generated paired heterogeneous images, we impose a distribution alignment in the latent space and a pairwise identity preserving in the image space.
Ranked #1 on
Face Verification
on CASIA NIR-VIS 2.0
Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing
It generates hashing bits by the output neurons of a deep hashing network.
