38 citations · 80 across the 36 of their papers we have counts for
15 papers · 1 filter
Resolving Endpoint Underfitting in Diffusion Bridges via Noise Alignment
Yurong Gao, Zicheng Zhang, Congying Han +2
Diffusion bridge models offer a powerful framework for connecting two data distributions, such as in image restoration and translation. Many existing methods learn this bridge by m…
DR-BFR: Degradation Representation with Diffusion Models for Blind Face Restoration
Xinmin Qiu, Bonan Li, Zicheng Zhang +2
Blind face restoration (BFR) is fundamentally challenged by the extensive range of degradation types and degrees that impact model generalization. Recent advancements in diffusion…
BlazeBVD: Make Scale-Time Equalization Great Again for Blind Video Deflickering
Xinmin Qiu, Congying Han, Zicheng Zhang +4
Developing blind video deflickering (BVD) algorithms to enhance video temporal consistency, is gaining importance amid the flourish of image processing and video generation. Howeve…
Learning Dynamic Tetrahedra for High-Quality Talking Head Synthesis
Zicheng Zhang, Ruobing Zheng, Ziwen Liu +7
Recent works in implicit representations, such as Neural Radiance Fields (NeRF), have advanced the generation of realistic and animatable head avatars from video sequences. These i…
Towards Consistent Video Editing with Text-to-Image Diffusion Models
Zicheng Zhang, Bonan Li, Xuecheng Nie +3
Existing works have advanced Text-to-Image (TTI) diffusion models for video editing in a one-shot learning manner. Despite their low requirements of data and computation, these met…
DiffBFR: Bootstrapping Diffusion Model Towards Blind Face Restoration
Xinmin Qiu, Congying Han, Zicheng Zhang +3
Blind face restoration (BFR) is important while challenging. Prior works prefer to exploit GAN-based frameworks to tackle this task due to the balance of quality and efficiency. Ho…
Transforming Radiance Field with Lipschitz Network for Photorealistic 3D Scene Stylization
Zicheng Zhang, Yinglu Liu, Congying Han +3
Recent advances in 3D scene representation and novel view synthesis have witnessed the rise of Neural Radiance Fields (NeRFs). Nevertheless, it is not trivial to exploit NeRF for t…
StyO: Stylize Your Face in Only One-shot
Bonan Li, Zicheng Zhang, Xuecheng Nie +4
This paper focuses on face stylization with a single artistic target. Existing works for this task often fail to retain the source content while achieving geometry variation. Here,…
Masked Reconstruction Contrastive Learning with Information Bottleneck Principle
Ziwen Liu, Bonan Li, Congying Han +2
Contrastive learning (CL) has shown great power in self-supervised learning due to its ability to capture insight correlations among large-scale data. Current CL models are biased…
Generalized One-shot Domain Adaptation of Generative Adversarial Networks
Zicheng Zhang, Yinglu Liu, Congying Han +3
The adaptation of a Generative Adversarial Network (GAN) aims to transfer a pre-trained GAN to a target domain with limited training data. In this paper, we focus on the one-shot c…
DropKey
Bonan Li, Yinhan Hu, Xuecheng Nie +4
In this paper, we focus on analyzing and improving the dropout technique for self-attention layers of Vision Transformer, which is important while surprisingly ignored by prior wor…
PetsGAN: Rethinking Priors for Single Image Generation
Zicheng Zhang, Yinglu Liu, Congying Han +3
Single image generation (SIG), described as generating diverse samples that have similar visual content with the given single image, is first introduced by SinGAN which builds a py…
ExSinGAN: Learning an Explainable Generative Model from a Single Image
ZiCheng Zhang, CongYing Han, TianDe Guo
Generating images from a single sample, as a newly developing branch of image synthesis, has attracted extensive attention. In this paper, we formulate this problem as sampling fro…
A Robust Point Sets Matching Method
Xiao Liu, Congying Han, Tiande Guo
Point sets matching method is very important in computer vision, feature extraction, fingerprint matching, motion estimation and so on. This paper proposes a robust point sets matc…
Fingerprint Classification Based on Depth Neural Network
Ruxin Wang, Congying Han, Yanping Wu +1
Fingerprint classification is an effective technique for reducing the candidate numbers of fingerprints in the stage of matching in automatic fingerprint identification system (AFI…