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Neural implicit surface reconstruction using volume rendering techniques has recently achieved significant advancements in creating high-fidelity surfaces from multiple 2D images. However, current methods primarily target scenes with…

Computer Vision and Pattern Recognition · Computer Science 2025-05-13 Lintao Xiang , Hongpei Zheng , Bailin Deng , Hujun Yin

Implicit neural rendering, especially Neural Radiance Field (NeRF), has shown great potential in novel view synthesis of a scene. However, current NeRF-based methods cannot enable users to perform user-controlled shape deformation in the…

Graphics · Computer Science 2022-05-11 Yu-Jie Yuan , Yang-Tian Sun , Yu-Kun Lai , Yuewen Ma , Rongfei Jia , Lin Gao

Recent methods for synthesizing 3D-aware face images have achieved rapid development thanks to neural radiance fields, allowing for high quality and fast inference speed. However, existing solutions for editing facial geometry and…

Graphics · Computer Science 2022-11-16 Kaiwen Jiang , Shu-Yu Chen , Feng-Lin Liu , Hongbo Fu , Lin Gao

The success of the Neural Radiance Fields (NeRF) in novel view synthesis has inspired researchers to propose neural implicit scene reconstruction. However, most existing neural implicit reconstruction methods optimize per-scene parameters…

Computer Vision and Pattern Recognition · Computer Science 2023-04-04 Yufan Ren , Fangjinhua Wang , Tong Zhang , Marc Pollefeys , Sabine Süsstrunk

High-fidelity reconstruction of head avatars from monocular videos is highly desirable for virtual human applications, but it remains a challenge in the fields of computer graphics and computer vision. In this paper, we propose a two-phase…

Graphics · Computer Science 2025-03-31 Pilseo Park , Ze Zhang , Michel Sarkis , Ning Bi , Xiaoming Liu , Yiying Tong

Creating high-quality controllable 3D human models from multi-view RGB videos poses a significant challenge. Neural radiance fields (NeRFs) have demonstrated remarkable quality in reconstructing and free-viewpoint rendering of static as…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Paul Knoll , Wieland Morgenstern , Anna Hilsmann , Peter Eisert

Neural Radiance Field (NeRF) has emerged as a leading technique for novel view synthesis, owing to its impressive photorealistic reconstruction and rendering capability. Nevertheless, achieving real-time NeRF rendering in large-scale scenes…

Computer Vision and Pattern Recognition · Computer Science 2025-03-31 Chaojian Li , Bichen Wu , Peter Vajda , Yingyan Celine Lin

Style transfer for human face has been widely researched in recent years. Majority of the existing approaches work in 2D image domain and have 3D inconsistency issue when applied on different viewpoints of the same face. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2023-11-23 Jianwei Feng , Prateek Singhal

Readily editable mesh blendshapes have been widely used in animation pipelines, while recent advancements in neural geometry and appearance representations have enabled high-quality inverse rendering. Building upon these observations, we…

Graphics · Computer Science 2024-08-21 Xin Ming , Jiawei Li , Jingwang Ling , Libo Zhang , Feng Xu

3D rendering of dynamic face captures is a challenging problem, and it demands improvements on several fronts$\unicode{x2014}$photorealism, efficiency, compatibility, and configurability. We present a novel representation that enables…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Safa C. Medin , Gengyan Li , Ruofei Du , Stephan Garbin , Philip Davidson , Gregory W. Wornell , Thabo Beeler , Abhimitra Meka

Existing neural reconstruction schemes such as Neural Radiance Field (NeRF) are largely focused on modeling opaque objects. We present a novel neural refractive field(NeReF) to recover wavefront of transparent fluids by simultaneously…

Computer Vision and Pattern Recognition · Computer Science 2022-03-09 Ziyu Wang , Wei Yang , Junming Cao , Lan Xu , Junqing Yu , Jingyi Yu

Embedding polygonal mesh assets within photorealistic Neural Radience Fields (NeRF) volumes, such that they can be rendered and their dynamics simulated in a physically consistent manner with the NeRF, is under-explored from the system…

Graphics · Computer Science 2023-09-12 Yi-Ling Qiao , Alexander Gao , Yiran Xu , Yue Feng , Jia-Bin Huang , Ming C. Lin

Neural radiance fields (NeRF) rely on volume rendering to synthesize novel views. Volume rendering requires evaluating an integral along each ray, which is numerically approximated with a finite sum that corresponds to the exact integral…

Computer Vision and Pattern Recognition · Computer Science 2024-01-22 Mikaela Angelina Uy , Kiyohiro Nakayama , Guandao Yang , Rahul Krishna Thomas , Leonidas Guibas , Ke Li

Volume rendering using neural fields has shown great promise in capturing and synthesizing novel views of 3D scenes. However, this type of approach requires querying the volume network at multiple points along each viewing ray in order to…

Computer Vision and Pattern Recognition · Computer Science 2021-11-08 Martin Piala , Ronald Clark

Neural Radiance Field (NeRF) has emerged as a compelling method to represent 3D objects and scenes for photo-realistic rendering. However, its implicit representation causes difficulty in manipulating the models like the explicit mesh…

Computer Vision and Pattern Recognition · Computer Science 2022-10-14 Jiaxiang Tang , Xiaokang Chen , Jingbo Wang , Gang Zeng

Neural Radiance Fields (NeRF) is a cutting-edge neural network-based technique for novel view synthesis in 3D reconstruction. However, its significant computational demands pose challenges for deployment on mobile devices. While mesh-based…

Graphics · Computer Science 2025-04-07 Zhe Wang , Yifei Zhu

Image-based 3D reconstruction has increasingly stunning results over the past few years with the latest improvements in computer vision and graphics. Geometry and topology are two fundamental concepts when dealing with 3D mesh structures.…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Gaëtan Landreau , Mohamed Tamaazousti

We propose an analysis-by-synthesis method for fast multi-view 3D reconstruction of opaque objects with arbitrary materials and illumination. State-of-the-art methods use both neural surface representations and neural rendering. While…

Computer Vision and Pattern Recognition · Computer Science 2022-12-09 Markus Worchel , Rodrigo Diaz , Weiwen Hu , Oliver Schreer , Ingo Feldmann , Peter Eisert

Neural Radiance Fields (NeRFs) have demonstrated amazing ability to synthesize images of 3D scenes from novel views. However, they rely upon specialized volumetric rendering algorithms based on ray marching that are mismatched to the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Zhiqin Chen , Thomas Funkhouser , Peter Hedman , Andrea Tagliasacchi

Novel view synthesis is a long-standing problem that revolves around rendering frames of scenes from novel camera viewpoints. Volumetric approaches provide a solution for modeling occlusions through the explicit 3D representation of the…

Computer Vision and Pattern Recognition · Computer Science 2023-03-06 Youssef Abdelkareem , Shady Shehata , Fakhri Karray