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Related papers: AD-NeRF: Audio Driven Neural Radiance Fields for T…

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While 2D generative adversarial networks have enabled high-resolution image synthesis, they largely lack an understanding of the 3D world and the image formation process. Thus, they do not provide precise control over camera viewpoint or…

Computer Vision and Pattern Recognition · Computer Science 2021-03-31 Katja Schwarz , Yiyi Liao , Michael Niemeyer , Andreas Geiger

We propose INFAMOUS-NeRF, an implicit morphable face model that introduces hypernetworks to NeRF to improve the representation power in the presence of many training subjects. At the same time, INFAMOUS-NeRF resolves the classic…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Andrew Hou , Feng Liu , Zhiyuan Ren , Michel Sarkis , Ning Bi , Yiying Tong , Xiaoming Liu

This paper presents a stylized novel view synthesis method. Applying state-of-the-art stylization methods to novel views frame by frame often causes jittering artifacts due to the lack of cross-view consistency. Therefore, this paper…

Computer Vision and Pattern Recognition · Computer Science 2022-07-07 Thu Nguyen-Phuoc , Feng Liu , Lei Xiao

While rendering and animation of photorealistic 3D human body models have matured and reached an impressive quality over the past years, modeling the spatial audio associated with such full body models has been largely ignored so far. In…

Sound · Computer Science 2024-07-23 Chao Huang , Dejan Markovic , Chenliang Xu , Alexander Richard

Neural radiance fields (NeRF) bring a new wave for 3D interactive experiences. However, as an important part of the immersive experiences, the defocus effects have not been fully explored within NeRF. Some recent NeRF-based methods generate…

Computer Vision and Pattern Recognition · Computer Science 2022-08-11 Yinhuai Wang , Shuzhou Yang , Yujie Hu , Jian Zhang

Large-scale 3D scene reconstruction and novel view synthesis are vital for autonomous vehicles, especially utilizing temporally sparse LiDAR frames. However, conventional explicit representations remain a significant bottleneck towards…

Computer Vision and Pattern Recognition · Computer Science 2024-02-15 Xiuzhong Hu , Guangming Xiong , Zheng Zang , Peng Jia , Yuxuan Han , Junyi Ma

The task of talking head generation is to synthesize a lip synchronized talking head video by inputting an arbitrary face image and audio clips. Most existing methods ignore the local driving information of the mouth muscles. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Sen Chen , Zhilei Liu , Jiaxing Liu , Zhengxiang Yan , Longbiao Wang

Neural radiance fields enable state-of-the-art photorealistic view synthesis. However, existing radiance field representations are either too compute-intensive for real-time rendering or require too much memory to scale to large scenes. We…

Computer Vision and Pattern Recognition · Computer Science 2023-02-24 Christian Reiser , Richard Szeliski , Dor Verbin , Pratul P. Srinivasan , Ben Mildenhall , Andreas Geiger , Jonathan T. Barron , Peter Hedman

In the rapidly evolving landscape of digital content creation, the demand for fast, convenient, and autonomous methods of crafting detailed 3D reconstructions of humans has grown significantly. Addressing this pressing need, our AirNeRF…

Robotics · Computer Science 2024-07-16 Alexey Kotcov , Maria Dronova , Vladislav Cheremnykh , Sausar Karaf , Dzmitry Tsetserukou

Talking head generation is to synthesize a lip-synchronized talking head video by inputting an arbitrary face image and corresponding audio clips. Existing methods ignore not only the interaction and relationship of cross-modal information,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Sen Chen , Zhilei Liu , Jiaxing Liu , Longbiao Wang

In recent years, the field of implicit neural representation has progressed significantly. Models such as neural radiance fields (NeRF), which uses relatively small neural networks, can represent high-quality scenes and achieve…

Computer Vision and Pattern Recognition · Computer Science 2022-04-01 David Dadon , Ohad Fried , Yacov Hel-Or

Neural Radiance Fields (NeRF) have emerged as a powerful tool for creating highly detailed and photorealistic scenes. Existing methods for NeRF-based 3D style transfer need extensive per-scene optimization for single or multiple styles,…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Adil Meric , Umut Kocasari , Matthias Nießner , Barbara Roessle

Domain scientists often face I/O and storage challenges when keeping raw data from large-scale simulations. Saving visualization images, albeit practical, is limited to preselected viewpoints, transfer functions, and simulation parameters.…

Graphics · Computer Science 2025-02-25 Siyuan Yao , Yunfei Lu , Chaoli Wang

We introduce DiffRF, a novel approach for 3D radiance field synthesis based on denoising diffusion probabilistic models. While existing diffusion-based methods operate on images, latent codes, or point cloud data, we are the first to…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Norman Müller , Yawar Siddiqui , Lorenzo Porzi , Samuel Rota Bulò , Peter Kontschieder , Matthias Nießner

Neural Radiance Field (NeRF) models are implicit neural scene representation methods that offer unprecedented capabilities in novel view synthesis. Semantically-aware NeRFs not only capture the shape and radiance of a scene, but also encode…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Yuzhe Zhu , Lile Cai , Kangkang Lu , Fayao Liu , Xulei Yang

We present Neural Voice Puppetry, a novel approach for audio-driven facial video synthesis. Given an audio sequence of a source person or digital assistant, we generate a photo-realistic output video of a target person that is in sync with…

Computer Vision and Pattern Recognition · Computer Science 2020-07-30 Justus Thies , Mohamed Elgharib , Ayush Tewari , Christian Theobalt , Matthias Nießner

Recent advances in deep learning for sequential data have given rise to fast and powerful models that produce realistic videos of talking humans. The state of the art in talking face generation focuses mainly on lip-syncing, being…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Georgios Milis , Panagiotis P. Filntisis , Anastasios Roussos , Petros Maragos

We present neural radiance fields (NeRF) with templates, dubbed Template-NeRF, for modeling appearance and geometry and generating dense shape correspondences simultaneously among objects of the same category from only multi-view posed…

Computer Vision and Pattern Recognition · Computer Science 2021-11-09 Jianfei Guo , Zhiyuan Yang , Xi Lin , Qingfu Zhang

People talk with diversified styles. For one piece of speech, different talking styles exhibit significant differences in the facial and head pose movements. For example, the "excited" style usually talks with the mouth wide open, while the…

Computer Vision and Pattern Recognition · Computer Science 2021-11-02 Haozhe Wu , Jia Jia , Haoyu Wang , Yishun Dou , Chao Duan , Qingshan Deng

We propose a neural talking-head video synthesis model and demonstrate its application to video conferencing. Our model learns to synthesize a talking-head video using a source image containing the target person's appearance and a driving…

Computer Vision and Pattern Recognition · Computer Science 2021-04-06 Ting-Chun Wang , Arun Mallya , Ming-Yu Liu