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We propose DriveAnyMesh, a method for driving mesh guided by monocular video. Current 4D generation techniques encounter challenges with modern rendering engines. Implicit methods have low rendering efficiency and are unfriendly to…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Yahao Shi , Yang Liu , Yanmin Wu , Xing Liu , Chen Zhao , Jie Luo , Bin Zhou

The task of novel view synthesis aims to generate unseen perspectives of an object or scene from a limited set of input images. Nevertheless, synthesizing novel views from a single image still remains a significant challenge in the realm of…

Computer Vision and Pattern Recognition · Computer Science 2023-10-05 Yifan Jiang , Hao Tang , Jen-Hao Rick Chang , Liangchen Song , Zhangyang Wang , Liangliang Cao

Recent remarkable advances in large-scale text-to-image diffusion models have inspired a significant breakthrough in text-to-3D generation, pursuing 3D content creation solely from a given text prompt. However, existing text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-11-10 Yang Chen , Yingwei Pan , Yehao Li , Ting Yao , Tao Mei

Design tools in the 3D industry, while powerful, are still tedious and labor-intensive when it comes to bringing a creative idea for a visual effect to life. In this position paper, we discussed how an infamous generative synthetic media,…

Human-Computer Interaction · Computer Science 2022-04-28 Julius Girbig , Changkun Ou , Sylvia Rothe

Modern 3D-GANs synthesize geometry and texture by training on large-scale datasets with a consistent structure. Training such models on stylized, artistic data, with often unknown, highly variable geometry, and camera information has not…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Rameen Abdal , Hsin-Ying Lee , Peihao Zhu , Menglei Chai , Aliaksandr Siarohin , Peter Wonka , Sergey Tulyakov

Existing approaches to 3D semantic urban scene generation predominantly rely on voxel-based representations, which are bound by fixed resolution, challenging to edit, and memory-intensive in their dense form. In contrast, we advocate for a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-26 Christina Ourania Tze , Daniel Dauner , Yiyi Liao , Dzmitry Tsishkou , Andreas Geiger

Image synthesis has attracted emerging research interests in academic and industry communities. Deep learning technologies especially the generative models greatly inspired controllable image synthesis approaches and applications, which aim…

Computer Vision and Pattern Recognition · Computer Science 2023-07-21 Shixiong Zhang , Jiao Li , Lu Yang

We present a novel method for populating 3D indoor scenes with virtual humans that can navigate in the environment and interact with objects in a realistic manner. Existing approaches rely on training sequences that contain captured human…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Kaifeng Zhao , Yan Zhang , Shaofei Wang , Thabo Beeler , Siyu Tang

Speech-driven 3D facial animation plays a key role in applications such as virtual avatars, gaming, and digital content creation. While existing methods have made significant progress in achieving accurate lip synchronization and generating…

Graphics · Computer Science 2025-07-16 Yifang Pan , Karan Singh , Luiz Gustavo Hafemann

We present an approach to infer a layer-structured 3D representation of a scene from a single input image. This allows us to infer not only the depth of the visible pixels, but also to capture the texture and depth for content in the scene…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Shubham Tulsiani , Richard Tucker , Noah Snavely

Creating and editing high-quality 3D content remains a central challenge in computer graphics. We address this challenge by introducing CompoSE, a novel method for Compositional Synthesis and Editing of 3D shapes via part-aware control. Our…

Graphics · Computer Science 2026-05-20 Habib Slim , Shariq Farooq Bhat , Mohamed Elhoseiny , Yifan Wang , Mike Roberts

To be widely adopted, 3D facial avatars must be animated easily, realistically, and directly from speech signals. While the best recent methods generate 3D animations that are synchronized with the input audio, they largely ignore the…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Radek Daněček , Kiran Chhatre , Shashank Tripathi , Yandong Wen , Michael J. Black , Timo Bolkart

Impressive progress has been made in audio-driven 3D facial animation recently, but synthesizing 3D talking-head with rich emotion is still unsolved. This is due to the lack of 3D generative models and available 3D emotional dataset with…

Computer Vision and Pattern Recognition · Computer Science 2021-04-27 Qianyun Wang , Zhenfeng Fan , Shihong Xia

We present a diffusion-based model for 3D-aware generative novel view synthesis from as few as a single input image. Our model samples from the distribution of possible renderings consistent with the input and, even in the presence of…

Computer Vision and Pattern Recognition · Computer Science 2023-04-06 Eric R. Chan , Koki Nagano , Matthew A. Chan , Alexander W. Bergman , Jeong Joon Park , Axel Levy , Miika Aittala , Shalini De Mello , Tero Karras , Gordon Wetzstein

Diffusion-based video generation techniques have significantly improved zero-shot talking-head avatar generation, enhancing the naturalness of both head motion and facial expressions. However, existing methods suffer from poor…

Graphics · Computer Science 2025-04-24 Lingzhou Mu , Baiji Liu , Ruonan Zhang , Guiming Mo , Jiawei Jin , Kai Zhang , Haozhi Huang

Creating realistic 3D objects and clothed avatars from a single RGB image is an attractive yet challenging problem. Due to its ill-posed nature, recent works leverage powerful prior from 2D diffusion models pretrained on large datasets.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Yuxuan Xue , Xianghui Xie , Riccardo Marin , Gerard Pons-Moll

Talking head generation is to generate video based on a given source identity and target motion. However, current methods face several challenges that limit the quality and controllability of the generated videos. First, the generated face…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Yue Gao , Yuan Zhou , Jinglu Wang , Xiao Li , Xiang Ming , Yan Lu

Automatically generating multiview illusions is a compelling challenge, where a single piece of visual content offers distinct interpretations from different viewing perspectives. Traditional methods, such as shadow art and wire art, create…

Computer Vision and Pattern Recognition · Computer Science 2025-06-09 Yue Feng , Vaibhav Sanjay , Spencer Lutz , Badour AlBahar , Songwei Ge , Jia-Bin Huang

High-quality 3D world models are pivotal for embodied intelligence and Artificial General Intelligence (AGI), underpinning applications such as AR/VR content creation and robotic navigation. Despite the established strong imaginative…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Yixiang Dai , Fan Jiang , Chiyu Wang , Mu Xu , Yonggang Qi

Although diffusion-based models can generate high-quality and high-resolution video sequences from textual or image inputs, they lack explicit integration of geometric cues when controlling scene lighting and visual appearance across…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Yuanze Lin , Yi-Wen Chen , Yi-Hsuan Tsai , Ronald Clark , Ming-Hsuan Yang
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