Search Results for author: Yujun Shen

Found 18 papers, 11 papers with code

Glancing at the Patch: Anomaly Localization With Global and Local Feature Comparison

no code implementations CVPR 2021 Shenzhi Wang, Liwei Wu, Lei Cui, Yujun Shen

More concretely, we employ a Local-Net and Global-Net to extract features from any individual patch and its surrounding respectively.

Anomaly Detection

CompConv: A Compact Convolution Module for Efficient Feature Learning

no code implementations19 Jun 2021 Chen Zhang, Yinghao Xu, Yujun Shen

Convolutional Neural Networks (CNNs) have achieved remarkable success in various computer vision tasks but rely on tremendous computational cost.

Low-Rank Subspaces in GANs

1 code implementation8 Jun 2021 Jiapeng Zhu, Ruili Feng, Yujun Shen, Deli Zhao, ZhengJun Zha, Jingren Zhou, Qifeng Chen

Concretely, given an arbitrary image and a region of interest (e. g., eyes of face images), we manage to relate the latent space to the image region with the Jacobian matrix and then use low-rank factorization to discover steerable latent subspaces.

Data-Efficient Instance Generation from Instance Discrimination

1 code implementation8 Jun 2021 Ceyuan Yang, Yujun Shen, Yinghao Xu, Bolei Zhou

Meanwhile, the learned instance discrimination capability from the discriminator is in turn exploited to encourage the generator for diverse generation.

Data Augmentation Image Generation

Unsupervised Image Transformation Learning via Generative Adversarial Networks

no code implementations13 Mar 2021 Kaiwen Zha, Yujun Shen, Bolei Zhou

In this work, we study the image transformation problem by learning the underlying transformations from a collection of images using Generative Adversarial Networks (GANs).

Image Generation

Improving the Fairness of Deep Generative Models without Retraining

1 code implementation9 Dec 2020 Shuhan Tan, Yujun Shen, Bolei Zhou

Generative Adversarial Networks (GANs) advance face synthesis through learning the underlying distribution of observed data.

Face Generation Face Recognition +2

Generative Hierarchical Features from Synthesizing Images

1 code implementation CVPR 2021 Yinghao Xu, Yujun Shen, Jiapeng Zhu, Ceyuan Yang, Bolei Zhou

Generative Adversarial Networks (GANs) have recently advanced image synthesis by learning the underlying distribution of the observed data.

Face Verification Image Classification +2

Closed-Form Factorization of Latent Semantics in GANs

8 code implementations CVPR 2021 Yujun Shen, Bolei Zhou

A rich set of interpretable dimensions has been shown to emerge in the latent space of the Generative Adversarial Networks (GANs) trained for synthesizing images.

Image Generation Image Manipulation

InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs

2 code implementations18 May 2020 Yujun Shen, Ceyuan Yang, Xiaoou Tang, Bolei Zhou

In this work, we propose a framework called InterFaceGAN to interpret the disentangled face representation learned by the state-of-the-art GAN models and study the properties of the facial semantics encoded in the latent space.

Face Generation GAN inversion

In-Domain GAN Inversion for Real Image Editing

3 code implementations ECCV 2020 Jiapeng Zhu, Yujun Shen, Deli Zhao, Bolei Zhou

A common practice of feeding a real image to a trained GAN generator is to invert it back to a latent code.

GAN inversion Image Interpolation +1

Residual Knowledge Distillation

no code implementations21 Feb 2020 Mengya Gao, Yujun Shen, Quanquan Li, Chen Change Loy

Knowledge distillation (KD) is one of the most potent ways for model compression.

Knowledge Distillation Model Compression

Image Processing Using Multi-Code GAN Prior

1 code implementation CVPR 2020 Jinjin Gu, Yujun Shen, Bolei Zhou

Such an over-parameterization of the latent space significantly improves the image reconstruction quality, outperforming existing competitors.

Blind Face Restoration Colorization +5

Semantic Hierarchy Emerges in Deep Generative Representations for Scene Synthesis

2 code implementations21 Nov 2019 Ceyuan Yang, Yujun Shen, Bolei Zhou

Despite the success of Generative Adversarial Networks (GANs) in image synthesis, there lacks enough understanding on what generative models have learned inside the deep generative representations and how photo-realistic images are able to be composed of the layer-wise stochasticity introduced in recent GANs.

Image Generation

Interpreting the Latent Space of GANs for Semantic Face Editing

4 code implementations CVPR 2020 Yujun Shen, Jinjin Gu, Xiaoou Tang, Bolei Zhou

In this work, we propose a novel framework, called InterFaceGAN, for semantic face editing by interpreting the latent semantics learned by GANs.

Face Generation GAN inversion +1

An Embarrassingly Simple Approach for Knowledge Distillation

1 code implementation5 Dec 2018 Mengya Gao, Yujun Shen, Quanquan Li, Junjie Yan, Liang Wan, Dahua Lin, Chen Change Loy, Xiaoou Tang

Knowledge Distillation (KD) aims at improving the performance of a low-capacity student model by inheriting knowledge from a high-capacity teacher model.

Face Recognition Knowledge Distillation +2

FaceFeat-GAN: a Two-Stage Approach for Identity-Preserving Face Synthesis

no code implementations4 Dec 2018 Yujun Shen, Bolei Zhou, Ping Luo, Xiaoou Tang

In the second stage, they compete in the image domain to render photo-realistic images that contain high diversity but preserve identity.

Face Generation

FaceID-GAN: Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis

no code implementations CVPR 2018 Yujun Shen, Ping Luo, Junjie Yan, Xiaogang Wang, Xiaoou Tang

Existing methods typically formulate GAN as a two-player game, where a discriminator distinguishes face images from the real and synthesized domains, while a generator reduces its discriminativeness by synthesizing a face of photo-realistic quality.

Face Generation

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