We propose NeRF-Insert, a NeRF editing framework that allows users to make high-quality local edits with a flexible level of control. Unlike previous work that relied on image-to-image …
Y Ji, H Zhu, J Tang, W Liu, Z Zhang, Y Xie, L Ma… - arXiv preprint arXiv …, 2024 - arxiv.org
The semantically interactive radiance field has always been an appealing task for its potential to facilitate user-friendly and automated real-world 3D scene understanding …
E Skartados, MK Yucel, B Manganelli… - Proceedings of the 15th …, 2024 - dl.acm.org
Neural Radiance Fields (NeRF) have quickly become the primary approach for 3D reconstruction and novel view synthesis in recent years due to their remarkable …
This study explores the utilization of Neural Radiance Fields (NeRFs), with a specific focus on the Instant NeRFs technique. The objective is to represent three-dimensional (3D) …
S Choi, H Song, J Kim, T Kim, H Do - arXiv preprint arXiv:2407.11793, 2024 - arxiv.org
Interactive segmentation of 3D Gaussians opens a great opportunity for real-time manipulation of 3D scenes thanks to the real-time rendering capability of 3D Gaussian …
M Wang, Q Yu, H Liu - Electronics, 2024 - mdpi.com
3D (Three-Dimensional) scene inpainting aims to remove objects from scenes and generate visually plausible regions to fill the hollows. Leveraging the foundation of NeRF (Neural …
Neural Radiance Fields (NeRFs) have become a powerful tool for modeling 3D scenes from multiple images. However, NeRFs remain difficult to segment into semantically meaningful …
L Wang, F Zhou, J Yin - arXiv preprint arXiv:2404.15891, 2024 - arxiv.org
Recent advancements in 3D reconstruction technologies have paved the way for high- quality and real-time rendering of complex 3D scenes. Despite these achievements, a …
Unveiling an empty street from crowded observations captured by in-car cameras is crucial for autonomous driving. However, removing all temporary static objects, such as stopped …