We present an algorithm for reconstructing the radiance field of a large-scale scene from a
single casually captured video. The task poses two core challenges. First, most existing …

We present an end-to-end system for the high-fidelity capture, model reconstruction, and
real-time rendering of walkable spaces in virtual reality using neural radiance fields. To this …

We present a new dataset called Real Acoustic Fields (RAF) that captures real acoustic
room data from multiple modalities. The dataset includes high-quality and densely captured …

We present EgoNeRF, a practical solution to reconstruct large-scale real-world
environments for VR assets. Given a few seconds of casually captured 360 video, EgoNeRF …

ABSTRACT 3D reconstruction plays an increasingly important role in modern
photogrammetric systems. Conventional satellite or aerial-based remote sensing (RS) …

Egocentric videos provide comprehensive contexts for user and scene understanding,
spanning multisensory perception to behavioral interaction. We propose Spherical World …

Omnidirectional cameras are extensively used in various applications to provide a wide field
of vision. However they face a challenge in synthesizing novel views due to the inevitable …

Abstract Today's Extended Reality (XR) applications that call for specific Diminished Reality
(DR) strategies to hide specific classes of objects are increasingly using 360° cameras …

We present a method to reconstruct indoor and outdoor static scene geometry and
appearance from an omnidirectional video moving in a small circular sweep. This setting is …

We propose a real-time visual-inertial dense SLAM system that utilizes the online data
streams from back-to-back dual fisheye cameras setup, providing 360◦ coverage of the …