paper-with-me

Papers

LayerPano3D: Layered 3D Panorama for Hyper-Immersive Scene Generation

2024-08-23 · Shuai Yang, Jing Tan, Mengchen Zhang, Tong Wu, Yixuan Li, Gordon Wetzstein, Ziwei Liu, Dahua Lin

3D immersive scene generation is a challenging yet critical task in computer vision and graphics. A desired virtual 3D scene should 1) exhibit omnidirectional view consistency, and 2) allow for free exploration in complex scene hierarchies. Existing methods either rely on successive scene expansion via inpainting or employ panorama representation to represent large FOV scene environments. However, the generated scene suffers from semantic drift during expansion and is unable to handle occlusion among scene hierarchies. To tackle these challenges, we introduce LayerPano3D, a novel framework for full-view, explorable panoramic 3D scene generation from a single text prompt. Our key insight is to decompose a reference 2D panorama into multiple layers at different depth levels, where each layer reveals the unseen space from the reference views via diffusion prior. LayerPano3D comprises multiple dedicated designs: 1) we introduce a novel text-guided anchor view synthesis pipeline for high-quality, consistent panorama generation. 2) We pioneer the Layered 3D Panorama as underlying representation to manage complex scene hierarchies and lift it into 3D Gaussians to splat detailed 360-degree omnidirectional scenes with unconstrained viewing paths. Extensive experiments demonstrate that our framework generates state-of-the-art 3D panoramic scene in both full view consistency and immersive exploratory experience. We believe that LayerPano3D holds promise for advancing 3D panoramic scene creation with numerous applications.

📄 PDF Abstract BibTeX arXiv:2408.13252

Code (0)

등록된 구현이 없습니다.

Tasks

Scene Generation

Methods 이 논문이 사용한 방법론

Diffusion Diffusion models generate samples by gradually removing noise from a signal, and their training objective can be expressed as a reweighted variational lower-bound…
Inpainting Train a convolutional neural network to generate the contents of an arbitrary image region conditioned on its surroundings.

Similar Papers 제목 키워드 기반

Scene4U: Hierarchical Layered 3D Scene Reconstruction from Single Panoramic Image for Your Immerse Exploration

2025-04-01 · CVPR 2025 1 · Zilong Huang, Jun He, Junyan Ye, Lihan Jiang 외

The reconstruction of immersive and realistic 3D scenes holds significant practical importance in various fields of computer vision and computer graphics. Typically, immersive and realistic scenes should be free from obs…

3D Scene ReconstructionLarge Language Model

TiP4GEN: Text to Immersive Panorama 4D Scene Generation

2025-08-17 · Ke Xing, Hanwen Liang, Dejia Xu, Yuyang Yin 외 arxiv

With the rapid advancement and widespread adoption of VR/AR technologies, there is a growing demand for the creation of high-quality, immersive dynamic scenes. However, existing generation works predominantly concentrate…

Scene GenerationVideo GenerationPoint Clouds

Stepper: Stepwise Immersive Scene Generation with Multiview Panoramas

2026-03-30 · Felix Wimbauer, Fabian Manhardt, Michael Oechsle, Nikolai Kalischek 외 arxiv

The synthesis of immersive 3D scenes from text is rapidly maturing, driven by novel video generative models and feed-forward 3D reconstruction, with vast potential in AR/VR and world modeling. While panoramic images have…

3D ReconstructionScene GenerationVideo Generation

PSGS: Text-driven Panorama Sliding Scene Generation via Gaussian Splatting

2026-01-31 · Xin Zhang, Shen Chen, Jiale Zhou, Lei Li arxiv

Generating realistic 3D scenes from text is crucial for immersive applications like VR, AR, and gaming. While text-driven approaches promise efficiency, existing methods suffer from limited 3D-text data and inconsistent …

Scene GenerationPoint Clouds

OmniX: From Unified Panoramic Generation and Perception to Graphics-Ready 3D Scenes

2025-10-30 · Yukun Huang, Jiwen Yu, Yanning Zhou, Jianan Wang 외 arxiv

There are two prevalent ways to constructing 3D scenes: procedural generation and 2D lifting. Among them, panorama-based 2D lifting has emerged as a promising technique, leveraging powerful 2D generative priors to produc…

Scene Generation