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Neural Radiance Fields (NeRF) revolutionized novel view synthesis in recent years by offering a new volumetric representation, which is compact and provides high-quality image rendering. However, the methods to edit those radiance fields…

Computer Vision and Pattern Recognition · Computer Science 2024-12-24 Arthur Hubert , Gamal Elghazaly , Raphael Frank

3D face generation has achieved high visual quality and 3D consistency thanks to the development of neural radiance fields (NeRF). Recently, to generate and edit 3D faces with NeRF representation, some methods are proposed and achieve good…

Computer Vision and Pattern Recognition · Computer Science 2023-02-21 Wenyang Zhou , Lu Yuan , Shuyu Chen , Lin Gao , Shimin Hu

Thermal imaging has a variety of applications, from agricultural monitoring to building inspection to imaging under poor visibility, such as in low light, fog, and rain. However, reconstructing thermal scenes in 3D presents several…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Yvette Y. Lin , Xin-Yi Pan , Sara Fridovich-Keil , Gordon Wetzstein

Neural Radiance Fields (NeRFs) typically struggle to reconstruct and render highly specular objects, whose appearance varies quickly with changes in viewpoint. Recent works have improved NeRF's ability to render detailed specular appearance…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Dor Verbin , Pratul P. Srinivasan , Peter Hedman , Ben Mildenhall , Benjamin Attal , Richard Szeliski , Jonathan T. Barron

With the advent of Neural Radiance Field (NeRF), representing 3D scenes through multiple observations has shown remarkable improvements in performance. Since this cutting-edge technique is able to obtain high-resolution renderings by…

Robotics · Computer Science 2023-09-18 Minjae Lee , Kyeongsu Kang , Hyeonwoo Yu

Neural Radiance Field (NeRF) has shown impressive performance in novel view synthesis via implicit scene representation. However, it usually suffers from poor scalability as requiring densely sampled images for each new scene. Several…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Muyu Xu , Fangneng Zhan , Jiahui Zhang , Yingchen Yu , Xiaoqin Zhang , Christian Theobalt , Ling Shao , Shijian Lu

Neural Radiance Fields (NeRFs) have demonstrated prominent performance in novel view synthesis. However, their input heavily relies on image acquisition under normal light conditions, making it challenging to learn accurate scene…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Min Wang , Xin Huang , Guoqing Zhou , Qifeng Guo , Qing Wang

This paper introduces a novel continual learning framework for synthesising novel views of multiple scenes, learning multiple 3D scenes incrementally, and updating the network parameters only with the training data of the upcoming new…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Yuze Wang , Junyi Wang , Chen Wang , Wantong Duan , Yongtang Bao , Yue Qi

Text-guided diffusion models have shown superior performance in image/video generation and editing. While few explorations have been performed in 3D scenarios. In this paper, we discuss three fundamental and interesting problems on this…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Gang Li , Heliang Zheng , Chaoyue Wang , Chang Li , Changwen Zheng , Dacheng Tao

Neural Radiance Fields (NeRF) achieve photo-realistic view synthesis with densely captured input images. However, the geometry of NeRF is extremely under-constrained given sparse views, resulting in significant degradation of novel view…

Computer Vision and Pattern Recognition · Computer Science 2022-09-13 Zheng Chen , Chen Wang , Yuan-Chen Guo , Song-Hai Zhang

Neural Radiance Field (NeRF) has gained considerable attention recently for 3D scene reconstruction and novel view synthesis due to its remarkable synthesis quality. However, image blurriness caused by defocus or motion, which often occurs…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Li Ma , Xiaoyu Li , Jing Liao , Qi Zhang , Xuan Wang , Jue Wang , Pedro V. Sander

The problem of modeling an animatable 3D human head avatar under light-weight setups is of significant importance but has not been well solved. Existing 3D representations either perform well in the realism of portrait images synthesis or…

Computer Vision and Pattern Recognition · Computer Science 2023-10-02 Xiaochen Zhao , Lizhen Wang , Jingxiang Sun , Hongwen Zhang , Jinli Suo , Yebin Liu

Reconstructing 3D human heads in low-view settings presents technical challenges, mainly due to the pronounced risk of overfitting with limited views and high-frequency signals. To address this, we propose geometry decomposition and adopt a…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Baixin Xu , Jiarui Zhang , Kwan-Yee Lin , Chen Qian , Ying He

Hyperspectral Imagery (HSI) has been used in many applications to non-destructively determine the material and/or chemical compositions of samples. There is growing interest in creating 3D hyperspectral reconstructions, which could provide…

Computer Vision and Pattern Recognition · Computer Science 2024-03-25 Gerry Chen , Sunil Kumar Narayanan , Thomas Gautier Ottou , Benjamin Missaoui , Harsh Muriki , Cédric Pradalier , Yongsheng Chen

Neural Radiance Fields (NeRF) have demonstrated exceptional capabilities in reconstructing complex scenes with high fidelity. However, NeRF's view dependency can only handle low-frequency reflections. It falls short when handling complex…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Chen Gao , Yipeng Wang , Changil Kim , Jia-Bin Huang , Johannes Kopf

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 NeRF has shown great success for neural reconstruction and rendering, its limited MLP capacity and long per-scene optimization times make it challenging to model large-scale indoor scenes. In contrast, classical 3D reconstruction…

Computer Vision and Pattern Recognition · Computer Science 2022-03-23 Xiaoshuai Zhang , Sai Bi , Kalyan Sunkavalli , Hao Su , Zexiang Xu

Recently, significant progress has been made in the study of methods for 3D reconstruction from multiple images using implicit neural representations, exemplified by the neural radiance field (NeRF) method. Such methods, which are based on…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Wooseok Kim , Taiki Fukiage , Takeshi Oishi

This paper investigates the transmission of three-dimensional (3D) human face content for immersive communication over a rate-constrained transmitter-receiver link. We propose a new framework named NeRF-SeCom, which leverages neural…

Image and Video Processing · Electrical Eng. & Systems 2024-07-22 Guanlin Wu , Zhonghao Lyu , Juyong Zhang , Jie Xu

Previous portrait image generation methods roughly fall into two categories: 2D GANs and 3D-aware GANs. 2D GANs can generate high fidelity portraits but with low view consistency. 3D-aware GAN methods can maintain view consistency but their…

Computer Vision and Pattern Recognition · Computer Science 2022-03-22 Jingxiang Sun , Xuan Wang , Yong Zhang , Xiaoyu Li , Qi Zhang , Yebin Liu , Jue Wang
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