Skip to main navigation Skip to search Skip to main content

360 + x: A Panoptic Multi-modal Scene Understanding Dataset

  • Hao Chen
  • , Yuqi Hou
  • , Chenyuan Qu
  • , Irene Testini
  • , Xiaohan Hong
  • , Jianbo Jiao

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

126 Downloads (Pure)

Abstract

Human perception of the world is shaped by a multitude of viewpoints and modalities. While many existing datasets focus on scene understanding from a certain perspective (e.g. egocentric or third-person views), our dataset offers a panoptic perspective (i.e. multiple viewpoints with multiple data modalities). Specifically, we encapsulate third-person panoramic and front views, as well as egocentric monocular/binocular views with rich modalities including video, multi-channel audio, directional binaural delay, location data and textual scene descriptions within each scene captured, presenting comprehensive observation of the world. To the best of our knowledge, this is the first database that covers multiple viewpoints with multiple data modalities to mimic how daily information is accessed in the real world. Through our benchmark analysis, we presented 5 different scene understanding tasks on the proposed 360+x dataset to evaluate the impact and benefit of each data modality and perspective in panoptic scene understanding. We hope this unique dataset could broaden the scope of comprehensive scene understanding and encourage the community to approach these problems from more diverse perspectives.
Original languageEnglish
Title of host publication2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages19373-19382
Number of pages10
ISBN (Electronic)9798350353006
ISBN (Print)9798350353013
DOIs
Publication statusPublished - 16 Sept 2024
Event2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition - Seattle Convention Center, Seattle, United States
Duration: 16 Jun 2024 → 22 Jun 2024
https://cvpr.thecvf.com
https://cvpr.thecvf.com/Conferences/2024

Publication series

NameConference on Computer Vision and Pattern Recognition (CVPR)
PublisherIEEE
ISSN (Print)1063-6919
ISSN (Electronic)2575-7075

Conference

Conference2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Abbreviated titleCVPR 2024
Country/TerritoryUnited States
CitySeattle
Period16/06/24 → 22/06/24
Internet address

Keywords

  • Computer vision
  • Annotations
  • Databases
  • Computational modeling
  • Self-supervised learning
  • Manuals
  • Benchmark testing

Fingerprint

Dive into the research topics of '360 + x: A Panoptic Multi-modal Scene Understanding Dataset'. Together they form a unique fingerprint.

Cite this