What is it about?

This research presents a new artificial intelligence method that can generate realistic 3D scene views from just a single photo. Normally, creating smooth and consistent scene views from one image is very difficult because parts of the scene are hidden or not visible. Our approach solves this by first imagining a full 360-degree panoramic view of the scene, then using this panorama to produce new perspectives as if a camera were moving through the space. By combining two advanced AI models — one for panorama generation and another for video-based view synthesis — the system can create continuous, coherent scene videos that stay geometrically aligned even for large camera movements. This technology can improve virtual reality, movie production, and simulation environments by making it easier to create immersive 3D experiences from minimal visual input.

Featured Image

Why is it important?

Creating realistic 3D environments from just one image has long been a challenge in computer vision and virtual reality. Most existing methods can only generate a few nearby views and often lose consistency when the viewpoint moves too far. Our work introduces a new way to bridge this gap by combining panoramic scene generation and video diffusion in a two-step process. This ensures that all generated views stay geometrically aligned, even when the virtual camera moves in loops or covers large areas. This is important because it brings AI-generated 3D scenes much closer to real-world visual experience. The approach can make virtual tours, metaverse environments, and autonomous robot simulations more reliable and lifelike — helping machines and humans better perceive and interact within digital 3D worlds.

Perspectives

Writing this paper was a rewarding experience because it brought together my long-term interests in 3D vision, generative AI, and immersive virtual environments. This work represents a key step toward connecting geometric understanding with creative visual generation — an area I have been passionate about since my early research in VR and 3D reconstruction. Collaborating with experts in both computer vision and graphics deepened my appreciation of how AI can bridge artistic creation and spatial reasoning. The project also inspired me to explore how such view synthesis techniques could support accessibility and educational tools, making virtual spaces more intuitive and inclusive. I believe this research will open new directions for combining geometry, generative modeling, and multimodal perception in the next generation of intelligent 3D systems.

Xueyang Kang
University of Melbourne

Read the Original

This page is a summary of: Look Beyond: Two-Stage Scene View Generation via Panorama and Video Diffusion, October 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3746027.3754779.
You can read the full text:

Read

Resources

Contributors

The following have contributed to this page