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Holo360D dataset advances panoramic 3D reconstruction with continuous trajectories

Researchers have introduced Holo360D, a new large-scale dataset designed to improve panoramic 3D reconstruction. This dataset features over 109,000 panoramas with registered point clouds, meshes, and camera poses, addressing limitations of existing datasets that use discrete camera locations. Holo360D provides continuous trajectories and high-completeness depth maps, collected using a 3D laser scanner and 360 camera, and enhanced with SLAM systems and a tailored post-processing pipeline. The dataset aims to establish a new benchmark for advancing feed-forward 3D reconstruction models, particularly in multi-view scenarios. AI

Summary written by gemini-2.5-flash-lite from 2 sources. How we write summaries →

IMPACT Provides a new benchmark and dataset to advance panoramic 3D reconstruction models.

RANK_REASON The cluster describes a new dataset and benchmark for 3D reconstruction published on arXiv.

Read on arXiv cs.CV →

COVERAGE [2]

  1. arXiv cs.CV TIER_1 · Jing Ou, Zidong Cao, Yinrui Ren, Zhuoxiao Li, Jinjing Zhu, Tongyan Hua, Shuai Zhang, Hui Xiong, Wufan Zhao ·

    Holo360D: A Large-Scale Real-World Dataset with Continuous Trajectories for Advancing Panoramic 3D Reconstruction and Beyond

    arXiv:2604.22482v1 Announce Type: new Abstract: While feed-forward 3D reconstruction models have advanced rapidly, they still exhibit degraded performance on panoramas due to spherical distortions. Moreover, existing panoramic 3D datasets are predominantly collected with 360 came…

  2. arXiv cs.CV TIER_1 · Wufan Zhao ·

    Holo360D: A Large-Scale Real-World Dataset with Continuous Trajectories for Advancing Panoramic 3D Reconstruction and Beyond

    While feed-forward 3D reconstruction models have advanced rapidly, they still exhibit degraded performance on panoramas due to spherical distortions. Moreover, existing panoramic 3D datasets are predominantly collected with 360 cameras fixed at discrete locations, resulting in di…