# Casual 6-DoF: free-viewpoint panorama using a handheld 360 camera

arXiv: https://arxiv.org/abs/2203.16756 · HTML: https://mlsanity.com/paper/2203.16756/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 50 references that are in the map.
- First posted on arXiv 31 Mar 2022.

## Builds on (most cited first, 13 of 13)

- [Nerfies: Deformable Neural Radiance Fields](https://mlsanity.com/paper/2011.12948/) (2020)
- [NeRF++: Analyzing and Improving Neural Radiance Fields](https://mlsanity.com/paper/2010.07492/) (2020)
- [MVSNet: Depth Inference for Unstructured Multi-view Stereo](https://mlsanity.com/paper/1804.02505/) (2018)
- [Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines](https://mlsanity.com/paper/1905.00889/) (2019)
- [Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference](https://mlsanity.com/paper/1902.10556/) (2019)
- [DeepView: View Synthesis with Learned Gradient Descent](https://mlsanity.com/paper/1906.07316/) (2019)
- [Free View Synthesis](https://mlsanity.com/paper/2008.05511/) (2020)
- [Stable View Synthesis](https://mlsanity.com/paper/2011.07233/) (2020)
- [Extreme View Synthesis](https://mlsanity.com/paper/1812.04777/) (2018)
- [MatryODShka: Real-time 6DoF Video View Synthesis using Multi-Sphere Images](https://mlsanity.com/paper/2008.06534/) (2020)
- [Spherical View Synthesis for Self-Supervised 360 Depth Estimation](https://mlsanity.com/paper/1909.08112/) (2019)
- [360SD-Net: 360deg Stereo Depth Estimation with Learnable Cost Volume](https://mlsanity.com/paper/1911.04460/) (2019)
- [A System for Acquiring, Processing, and Rendering Panoramic Light Field Stills for Virtual Reality](https://mlsanity.com/paper/1810.08860/) (2018)

## Built on by (most cited first, 7 of 7)

- [PanSplat: 4K Panorama Synthesis with Feed-Forward Gaussian Splatting](https://mlsanity.com/paper/2412.12096/) (2024)
- [ODGS: 3D Scene Reconstruction from Omnidirectional Images with 3D Gaussian Splattings](https://mlsanity.com/paper/2410.20686/) (2024)
- [Make Your Brief Stroke Real and Stereoscopic: 3D-Aware Simplified Sketch to Portrait Generation](https://mlsanity.com/paper/2302.06857/) (2023)
- [You Need a Transition Plane: Bridging Continuous Panoramic 3D Reconstruction with Perspective Gaussian Splatting](https://mlsanity.com/paper/2504.09062/) (2025)
- [PackUV: Packed Gaussian UV Maps for 4D Volumetric Video](https://mlsanity.com/paper/2602.23040/) (2026)
- [ImmersiveNeRF: Hybrid Radiance Fields for Unbounded Immersive Light Field Reconstruction](https://mlsanity.com/paper/2309.01374/) (2023)
- [Mover360: Controllable Object Manipulation in 360deg Panoramic Images](https://mlsanity.com/paper/2608.23238/) (2026)

## Abstract (arXiv)

Six degrees-of-freedom (6-DoF) video provides telepresence by enabling users to move around in the captured scene with a wide field of regard. Compared to methods requiring sophisticated camera setups, the image-based rendering method based on photogrammetry can work with images captured with any poses, which is more suitable for casual users. However, existing image-based rendering methods are based on perspective images. When used to reconstruct 6-DoF views, it often requires capturing hundreds of images, making data capture a tedious and time-consuming process. In contrast to traditional perspective images, 360deg images capture the entire surrounding view in a single shot, thus, providing a faster capturing process for 6-DoF view reconstruction. This paper presents a novel method to provide 6-DoF experiences over a wide area using an unstructured collection of 360deg panoramas captured by a conventional 360deg camera. Our method consists of 360deg data capturing, novel depth estimation to produce a high-quality spherical depth panorama, and high-fidelity free-viewpoint generation. We compared our method against state-of-the-art methods, using data captured in various environments. Our method shows better visual quality and robustness in the tested scenes.