Labeling Panoramas with Spherical Hourglass Networks

2018-09-06 · Carlos Esteves, Kostas Daniilidis, Ameesh Makadia

With the recent proliferation of consumer-grade 360{\deg} cameras, it is worth revisiting visual perception challenges with spherical cameras given the potential benefit of their global field of view. To this end we introduce a spherical convolutional hourglass network (SCHN) for the dense labeling on the sphere. The SCHN is invariant to camera orientation (lifting the usual requirement for `upright' panoramic images), and its design is scalable for larger practical datasets. Initial experiments show promising results on a spherical semantic segmentation task.

📄 PDF Abstract BibTeX arXiv:1809.02123

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Tasks

Semantic Segmentation

PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas

2023-06-02 · NeurIPS 2023 11 · Zheng Chen, Yan-Pei Cao, Yuan-Chen Guo, Chen Wang 외

Achieving an immersive experience enabling users to explore virtual environments with six degrees of freedom (6DoF) is essential for various applications such as virtual reality (VR). Wide-baseline panoramas are commonly…

Depth Estimation

Snap Angle Prediction for 360$^{\circ}$ Panoramas

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360$^{\circ}$ panoramas are a rich medium, yet notoriously difficult to visualize in the 2D image plane. We explore how intelligent rotations of a spherical image may enable content-aware projection with fewer perceptibl…

Prediction reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

Snap Angle Prediction for 360Â° Panoramas

2018-09-01 · ECCV 2018 9 · Bo Xiong, Kristen Grauman

360Â° panoramas are a rich medium, yet notoriously difficult to visualize in the 2D image plane. We explore how intelligent rotations of a spherical image may enable content-aware projection with fewer perceptible disto…

Prediction reinforcement-learning Reinforcement Learning Reinforcement Learning (RL)

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2021-02-07 · Nikolaos Zioulis, Federico Alvarez, Dimitrios Zarpalas, Petros Daras

It has been shown that global scene understanding tasks like layout estimation can benefit from wider field of views, and specifically spherical panoramas. While much progress has been made recently, all previous approac…

Keypoint Estimation Scene Understanding

Rotation-Invariant Spherical Watermarking via Third-Order SO(3) Representation Coupling

2026-05-26 · Pengzhen Chen, Yanwei Liu, Xiaoyan Gu, Antonios Argyriou 외 arxiv

Reliable watermarking of panoramic imagery is fundamentally challenged by arbitrary 3D rotations. As panoramas are defined on the sphere, they naturally transform under the action of $SO(3)$, rendering conventional plana…