Search Results for author: Qingyan Bai

Found 8 papers, 5 papers with code

Real-time 3D-aware Portrait Editing from a Single Image

no code implementations21 Feb 2024 Qingyan Bai, Yinghao Xu, Zifan Shi, Hao Ouyang, Qiuyu Wang, Ceyuan Yang, Xuan Wang, Gordon Wetzstein, Yujun Shen, Qifeng Chen

This work presents 3DPE, a practical tool that can efficiently edit a face image following given prompts, like reference images or text descriptions, in the 3D-aware manner.

CoDeF: Content Deformation Fields for Temporally Consistent Video Processing

1 code implementation15 Aug 2023 Hao Ouyang, Qiuyu Wang, Yuxi Xiao, Qingyan Bai, Juntao Zhang, Kecheng Zheng, Xiaowei Zhou, Qifeng Chen, Yujun Shen

We present the content deformation field CoDeF as a new type of video representation, which consists of a canonical content field aggregating the static contents in the entire video and a temporal deformation field recording the transformations from the canonical image (i. e., rendered from the canonical content field) to each individual frame along the time axis. Given a target video, these two fields are jointly optimized to reconstruct it through a carefully tailored rendering pipeline. We advisedly introduce some regularizations into the optimization process, urging the canonical content field to inherit semantics (e. g., the object shape) from the video. With such a design, CoDeF naturally supports lifting image algorithms for video processing, in the sense that one can apply an image algorithm to the canonical image and effortlessly propagate the outcomes to the entire video with the aid of the temporal deformation field. We experimentally show that CoDeF is able to lift image-to-image translation to video-to-video translation and lift keypoint detection to keypoint tracking without any training. More importantly, thanks to our lifting strategy that deploys the algorithms on only one image, we achieve superior cross-frame consistency in processed videos compared to existing video-to-video translation approaches, and even manage to track non-rigid objects like water and smog. Project page can be found at https://qiuyu96. github. io/CoDeF/.

Image-to-Image Translation Keypoint Detection +1

GLeaD: Improving GANs with A Generator-Leading Task

1 code implementation CVPR 2023 Qingyan Bai, Ceyuan Yang, Yinghao Xu, Xihui Liu, Yujiu Yang, Yujun Shen

Generative adversarial network (GAN) is formulated as a two-player game between a generator (G) and a discriminator (D), where D is asked to differentiate whether an image comes from real data or is produced by G. Under such a formulation, D plays as the rule maker and hence tends to dominate the competition.

domain classification Generative Adversarial Network +1

High-fidelity GAN Inversion with Padding Space

1 code implementation21 Mar 2022 Qingyan Bai, Yinghao Xu, Jiapeng Zhu, Weihao Xia, Yujiu Yang, Yujun Shen

In this work, we propose to involve the padding space of the generator to complement the latent space with spatial information.

Generative Adversarial Network Image Manipulation +1

StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN

1 code implementation8 Mar 2022 Fei Yin, Yong Zhang, Xiaodong Cun, Mingdeng Cao, Yanbo Fan, Xuan Wang, Qingyan Bai, Baoyuan Wu, Jue Wang, Yujiu Yang

Our framework elevates the resolution of the synthesized talking face to 1024*1024 for the first time, even though the training dataset has a lower resolution.

Facial Editing Talking Face Generation +1

Identity-guided Face Generation with Multi-modal Contour Conditions

no code implementations10 Oct 2021 Qingyan Bai, Weihao Xia, Fei Yin, Yujiu Yang

Concretely, we propose a novel dual-encoder architecture, in which an identity encoder extracts the identity-related feature, accompanied by a main encoder to obtain the rough contour information and further fuse all the information together.

Face Generation Image Restoration

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