285 citations · 670 across the 26 of their papers we have counts for
20 papers · 1 filter
MODIFY: Model-driven Face Stylization without Style Images
Yuhe Ding, Jian Liang, Jie Cao +2
Existing face stylization methods always acquire the presence of the target (style) domain during the translation process, which violates privacy regulations and limits their appli…
ScoreMix: A Scalable Augmentation Strategy for Training GANs with Limited Data
Jie Cao, Mandi Luo, Junchi Yu +2
Generative Adversarial Networks (GANs) typically suffer from overfitting when limited training data is available. To facilitate GAN training, current methods propose to use data-sp…
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification
Jijie Wu, Dongliang Chang, Aneeshan Sain +5
The main challenge for fine-grained few-shot image classification is to learn feature representations with higher inter-class and lower intra-class variations, with a mere few labe…
Vision Transformer with Super Token Sampling
Huaibo Huang, Xiaoqiang Zhou, Jie Cao +2
Vision transformer has achieved impressive performance for many vision tasks. However, it may suffer from high redundancy in capturing local features for shallow layers. Local self…
Styleverse: Towards Identity Stylization across Heterogeneous Domains
Jia Li, Jie Cao, JunXian Duan +1
We propose a new challenging task namely IDentity Stylization (IDS) across heterogeneous domains. IDS focuses on stylizing the content identity, rather than completely swapping it…
Video Super-Resolution Transformer
Jiezhang Cao, Yawei Li, Kai Zhang +1
Video super-resolution (VSR), with the aim to restore a high-resolution video from its corresponding low-resolution version, is a spatial-temporal sequence prediction problem. Rece…
LocalViT: Analyzing Locality in Vision Transformers
Yawei Li, Kai Zhang, Jiezhang Cao +4
The aim of this paper is to study the influence of locality mechanisms in vision transformers. Transformers originated from machine translation and are particularly good at modelli…
ReMix: Towards Image-to-Image Translation with Limited Data
Jie Cao, Luanxuan Hou, Ming-Hsuan Yang +2
Image-to-image (I2I) translation methods based on generative adversarial networks (GANs) typically suffer from overfitting when limited training data is available. In this work, we…
Net: Augmented Parallel-Pyramid Net for Attention Guided Pose Estimation
Luanxuan Hou, Jie Cao, Yuan Zhao +3
We propose an augmented Parallel-Pyramid Net () with feature refinement by dilated bottleneck and attention module. During data preprocessing, we proposed a differentiable…
Reference-guided Face Component Editing
Qiyao Deng, Jie Cao, Yunfan Liu +3
Face portrait editing has achieved great progress in recent years. However, previous methods either 1) operate on pre-defined face attributes, lacking the flexibility of controllin…
Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation
Luanxuan Hou, Jie Cao, Yuan Zhao +4
The target of human pose estimation is to determine body part or joint locations of each person from an image. This is a challenging problems with wide applications. To address thi…
Informative Sample Mining Network for Multi-Domain Image-to-Image Translation
Jie Cao, Huaibo Huang, Yi Li +2
The performance of multi-domain image-to-image translation has been significantly improved by recent progress in deep generative models. Existing approaches can use a unified model…
Learning 3D Human Shape and Pose from Dense Body Parts
Hongwen Zhang, Jie Cao, Guo Lu +2
Reconstructing 3D human shape and pose from monocular images is challenging despite the promising results achieved by the most recent learning-based methods. The commonly occurred…
PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer
Wentao Jiang, Si Liu, Chen Gao +4
In this paper, we address the makeup transfer task, which aims to transfer the makeup from a reference image to a source image. Existing methods have achieved promising progress in…
Biphasic Learning of GANs for High-Resolution Image-to-Image Translation
Jie Cao, Huaibo Huang, Yi Li +3
Despite that the performance of image-to-image translation has been significantly improved by recent progress in generative models, current methods still suffer from severe degrada…
Cross-spectral Face Completion for NIR-VIS Heterogeneous Face Recognition
Ran He, Jie Cao, Lingxiao Song +2
Near infrared-visible (NIR-VIS) heterogeneous face recognition refers to the process of matching NIR to VIS face images. Current heterogeneous methods try to extend VIS face recogn…
Geometry-Aware Face Completion and Editing
Linsen Song, Jie Cao, Linxiao Song +2
Face completion is a challenging generation task because it requires generating visually pleasing new pixels that are semantically consistent with the unmasked face region. This pa…
Learning a High Fidelity Pose Invariant Model for High-resolution Face Frontalization
Jie Cao, Yibo Hu, Hongwen Zhang +2
Face frontalization refers to the process of synthesizing the frontal view of a face from a given profile. Due to self-occlusion and appearance distortion in the wild, it is extrem…
Load Balanced GANs for Multi-view Face Image Synthesis
Jie Cao, Yibo Hu, Bing Yu +2
Multi-view face synthesis from a single image is an ill-posed problem and often suffers from serious appearance distortion. Producing photo-realistic and identity preserving multi-…
Recent Progress of Face Image Synthesis
Zhihe Lu, Zhihang Li, Jie Cao +2
Face synthesis has been a fascinating yet challenging problem in computer vision and machine learning. Its main research effort is to design algorithms to generate photo-realistic…