104 citations · 217 across the 27 of their papers we have counts for
15 papers · 1 filter
ToonTalker: Cross-Domain Face Reenactment
Yuan Gong, Yong Zhang, Xiaodong Cun +5
We target cross-domain face reenactment in this paper, i.e., driving a cartoon image with the video of a real person and vice versa. Recently, many works have focused on one-shot t…
Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation
Yingqing He, Menghan Xia, Haoxin Chen +8
Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these c…
NOFA: NeRF-based One-shot Facial Avatar Reconstruction
Wangbo Yu, Yanbo Fan, Yong Zhang +8
3D facial avatar reconstruction has been a significant research topic in computer graphics and computer vision, where photo-realistic rendering and flexible controls over poses and…
Make-Your-Video: Customized Video Generation Using Textual and Structural Guidance
Jinbo Xing, Menghan Xia, Yuxin Liu +9
Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential t…
Inserting Anybody in Diffusion Models via Celeb Basis
Ge Yuan, Xiaodong Cun, Yong Zhang +5
Exquisite demand exists for customizing the pretrained large text-to-image model, , Stable Diffusion, to generate innovative concepts, such as the users themselves.…
TaleCrafter: Interactive Story Visualization with Multiple Characters
Yuan Gong, Youxin Pang, Xiaodong Cun +8
Accurate Story visualization requires several necessary elements, such as identity consistency across frames, the alignment between plain text and visual content, and a reasonable…
High-Fidelity Clothed Avatar Reconstruction from a Single Image
Tingting Liao, Xiaomei Zhang, Yuliang Xiu +7
This paper presents a framework for efficient 3D clothed avatar reconstruction. By combining the advantages of the high accuracy of optimization-based methods and the efficiency of…
CoordFill: Efficient High-Resolution Image Inpainting via Parameterized Coordinate Querying
Weihuang Liu, Xiaodong Cun, Chi-Man Pun +3
Image inpainting aims to fill the missing hole of the input. It is hard to solve this task efficiently when facing high-resolution images due to two reasons: (1) Large reception fi…
FateZero: Fusing Attentions for Zero-shot Text-based Video Editing
Chenyang Qi, Xiaodong Cun, Yong Zhang +4
The diffusion-based generative models have achieved remarkable success in text-based image generation. However, since it contains enormous randomness in generation progress, it is…
VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild
Kun Cheng, Xiaodong Cun, Yong Zhang +6
We present VideoReTalking, a new system to edit the faces of a real-world talking head video according to input audio, producing a high-quality and lip-syncing output video even wi…
High-fidelity Facial Avatar Reconstruction from Monocular Video with Generative Priors
Yunpeng Bai, Yanbo Fan, Xuan Wang +4
High-fidelity facial avatar reconstruction from a monocular video is a significant research problem in computer graphics and computer vision. Recently, Neural Radiance Field (NeRF)…
Latent Video Diffusion Models for High-Fidelity Long Video Generation
Yingqing He, Tianyu Yang, Yong Zhang +2
AI-generated content has attracted lots of attention recently, but photo-realistic video synthesis is still challenging. Although many attempts using GANs and autoregressive models…
Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars
Jingxiang Sun, Xuan Wang, Lizhen Wang +4
3D-aware generative adversarial networks (GANs) synthesize high-fidelity and multi-view-consistent facial images using only collections of single-view 2D imagery. Towards fine-grai…
SemAug: Semantically Meaningful Image Augmentations for Object Detection Through Language Grounding
Morgan Heisler, Amin Banitalebi-Dehkordi, Yong Zhang
Data augmentation is an essential technique in improving the generalization of deep neural networks. The majority of existing image-domain augmentations either rely on geometric an…
AuxMix: Semi-Supervised Learning with Unconstrained Unlabeled Data
Amin Banitalebi-Dehkordi, Pratik Gujjar, Yong Zhang
Semi-supervised learning (SSL) has seen great strides when labeled data is scarce but unlabeled data is abundant. Critically, most recent work assume that such unlabeled data is dr…