Publikation
ToF-360 – A Panoramic Time-of-flight RGB-D Dataset for Single Capture Indoor Semantic 3D Reconstruction
Hideaki Kanayama; Mahdi Chamseddine; Suresh Guttikonda; So Okumura; Soichiro Yokota; Didier Stricker; Jason Raphael Rambach
In: IEEE/CVF (Hrsg.). 21st. CVPR Workshop on Perception Beyond the Visible Spectrum (PBVS-2025), June 11-15, Nashville, Tennessee, USA, IEEE, 2025.
Zusammenfassung
3D scene understanding is a key research topic for various
automation areas. Many RGB-D datasets today focus on
reconstruction of entire scenes. However, their scanning
processes are time-consuming, requiring multiple or continuous
recordings using a scanner with a limited angle of
view. Such datasets often contain data affected by stitching
artifacts or poor quality annotation masks projected directly
from 3D to image. In this paper, we present ToF-360. This
is the first RGB-D dataset obtained by a unique Time-of-
Flight (ToF) sensor capable of 360→ omnidirectional RGB-D
scanning within seconds. In addition to the raw data in a
fisheye format and equi-rectangular projection (ERP) images
from the device, we provide manually labeled high-quality,
pixel-level, 2D semantics and room layout annotations and
introduce a benchmark for three practical tasks: 2D semantic
segmentation, 3D semantic segmentation, and layout
estimation. We demonstrate that our dataset helps to better
represent real-world scenarios and push the limits of existing
state-of-the-art methods. The dataset is publicly available at
https://doi.org/10.57967/hf/5074.