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Neural rendering has garnered substantial attention owing to its capacity for creating realistic 3D scenes. However, its applicability to extensive scenes remains challenging, with limitations in effectiveness. In this work, we propose the…

Computer Vision and Pattern Recognition · Computer Science 2023-08-31 Zhihao Jia , Bing Wang , Changhao Chen

Mesh reconstruction from Neural Radiance Fields (NeRF) is widely used in 3D reconstruction and has been applied across numerous domains. However, existing methods typically rely solely on the given training set images, which restricts…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Haoyang Wang , Liming Liu , Xinggong Zhang

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

Novel View Synthesis (NVS) for street scenes play a critical role in the autonomous driving simulation. The current mainstream technique to achieve it is neural rendering, such as Neural Radiance Fields (NeRF) and 3D Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Zhongrui Yu , Haoran Wang , Jinze Yang , Hanzhang Wang , Zeke Xie , Yunfeng Cai , Jiale Cao , Zhong Ji , Mingming Sun

Multi-view surface reconstruction is an ill-posed, inverse problem in 3D vision research. It involves modeling the geometry and appearance with appropriate surface representations. Most of the existing methods rely either on explicit…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Zhangjin Huang , Zhihao Liang , Haojie Zhang , Yangkai Lin , Kui Jia

Recovering the shape and appearance of real-world objects from natural 2D images is a long-standing and challenging inverse rendering problem. In this paper, we introduce a novel hybrid differentiable rendering method to efficiently…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Xiangyang Zhu , Yiling Pan , Bailin Deng , Bin Wang

We present a novel method for performing flexible, 3D-aware image content manipulation while enabling high-quality novel view synthesis. While NeRF-based approaches are effective for novel view synthesis, such models memorize the radiance…

Computer Vision and Pattern Recognition · Computer Science 2022-04-25 Verica Lazova , Vladimir Guzov , Kyle Olszewski , Sergey Tulyakov , Gerard Pons-Moll

Current methods for 3D reconstruction and environmental mapping frequently face challenges in achieving high precision, highlighting the need for practical and effective solutions. In response to this issue, our study introduces FlyNeRF, a…

Robotics · Computer Science 2024-04-22 Maria Dronova , Vladislav Cheremnykh , Alexey Kotcov , Aleksey Fedoseev , Dzmitry Tsetserukou

Neural radiance fields (NeRFs) have gained popularity in the autonomous driving (AD) community. Recent methods show NeRFs' potential for closed-loop simulation, enabling testing of AD systems, and as an advanced training data augmentation…

Computer Vision and Pattern Recognition · Computer Science 2024-04-19 Adam Tonderski , Carl Lindström , Georg Hess , William Ljungbergh , Lennart Svensson , Christoffer Petersson

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

High-fidelity street scene reconstruction is pivotal for end-to-end autonomous driving simulation, where novel-view synthesis (NVS) and time-varying information modeling are two fundamental capabilities to facilitate closed-loop training.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Bowyn Tan , Yutong Xie , Bai Huang , Fan Luo , Xiao Li , Naizheng Wang , Yang Guan , Shengbo Eben Li

Neural Radiance Fields (NeRF) have emerged as a powerful paradigm for 3D scene representation, offering high-fidelity renderings and reconstructions from a set of sparse and unstructured sensor data. In the context of autonomous robotics,…

Robotics · Computer Science 2024-12-09 Yuhang Ming , Xingrui Yang , Weihan Wang , Zheng Chen , Jinglun Feng , Yifan Xing , Guofeng Zhang

We present a novel paradigm of building an animatable 3D human representation from a monocular video input, such that it can be rendered in any unseen poses and views. Our method is based on a dynamic Neural Radiance Field (NeRF) rigged by…

Computer Vision and Pattern Recognition · Computer Science 2022-08-19 Gusi Te , Xiu Li , Xiao Li , Jinglu Wang , Wei Hu , Yan Lu

Reconstruction of deformable scenes from endoscopic videos is important for many applications such as intraoperative navigation, surgical visual perception, and robotic surgery. It is a foundational requirement for realizing autonomous…

Computer Vision and Pattern Recognition · Computer Science 2025-03-19 Shreya Saha , Zekai Liang , Shan Lin , Jingpei Lu , Michael Yip , Sainan Liu

The quality of three-dimensional reconstruction is a key factor affecting the effectiveness of its application in areas such as virtual reality (VR) and augmented reality (AR) technologies. Neural Radiance Fields (NeRF) can generate…

Computer Vision and Pattern Recognition · Computer Science 2023-06-09 Qianqiu Tan , Tao Liu , Yinling Xie , Shuwan Yu , Baohua Zhang

Driving simulators play a large role in developing and testing new intelligent vehicle systems. The visual fidelity of the simulation is critical for building vision-based algorithms and conducting human driver experiments. Low visual…

Computer Vision and Pattern Recognition · Computer Science 2022-07-22 Ekim Yurtsever , Dongfang Yang , Ibrahim Mert Koc , Keith A. Redmill

Reconstruction and intrinsic decomposition of scenes from captured imagery would enable many applications such as relighting and virtual object insertion. Recent NeRF based methods achieve impressive fidelity of 3D reconstruction, but bake…

Computer Vision and Pattern Recognition · Computer Science 2023-04-07 Zian Wang , Tianchang Shen , Jun Gao , Shengyu Huang , Jacob Munkberg , Jon Hasselgren , Zan Gojcic , Wenzheng Chen , Sanja Fidler

Recent works in volume rendering, \textit{e.g.} NeRF and 3D Gaussian Splatting (3DGS), significantly advance the rendering quality and efficiency with the help of the learned implicit neural radiance field or 3D Gaussians. Rendering on top…

Computer Vision and Pattern Recognition · Computer Science 2026-02-06 Xiaobiao Du , Yida Wang , Xin Yu

Industrial 3D face assets creation typically reconstructs topology-consistent face meshes from multi-view images for downstream production. However, high-quality reconstruction usually requires manual processing or specific capture…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Yating Wang , Ran Yi , Xiaoning Lei , Ke Fan , Jinkun Hao , Lizhuang Ma

Synthesizing free-view photo-realistic images is an important task in multimedia. With the development of advanced driver assistance systems~(ADAS) and their applications in autonomous vehicles, experimenting with different scenarios…

Computer Vision and Pattern Recognition · Computer Science 2022-05-13 Zhuopeng Li , Lu Li , Zeyu Ma , Ping Zhang , Junbo Chen , Jianke Zhu