|
| | | | |
| | | |
| Stat |
Members: 3669
Articles: 2'599'751
Articles rated: 2609
22 March 2025 |
|
| | | | |
|
Article overview
| |
|
|
Single-view 3D Scene Reconstruction with High-fidelity Shape and Texture | | Yixin Chen
; Junfeng Ni
; Nan Jiang
; Yaowei Zhang
; Yixin Zhu
; Siyuan Huang
; | | Date: |
1 Nov 2023 | | Abstract: | Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, overlooking object appearances and fine shape details. To address these challenges, we propose a novel framework for simultaneous high-fidelity recovery of object shapes and textures from single-view images. Our approach utilizes the proposed Single-view neural implicit Shape and Radiance field (SSR) representations to leverage both explicit 3D shape supervision and volume rendering of color, depth, and surface normal images. To overcome shape-appearance ambiguity under partial observations, we introduce a two-stage learning curriculum incorporating both 3D and 2D supervisions. A distinctive feature of our framework is its ability to generate fine-grained textured meshes while seamlessly integrating rendering capabilities into the single-view 3D reconstruction model. This integration enables not only improved textured 3D object reconstruction by 27.7% and 11.6% on the 3D-FRONT and Pix3D datasets, respectively, but also supports the rendering of images from novel viewpoints. Beyond individual objects, our approach facilitates composing object-level representations into flexible scene representations, thereby enabling applications such as holistic scene understanding and 3D scene editing. We conduct extensive experiments to demonstrate the effectiveness of our method. | | Source: | arXiv, 2311.00457 | | Services: | Forum | Review | PDF | Favorites | |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
|
| |
|
|
|
REGISTER