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360PanT: Training-Free Text-Driven 360-Degree Panorama-to-Panorama Translation

Wang, H; Xue, JH; (2025) 360PanT: Training-Free Text-Driven 360-Degree Panorama-to-Panorama Translation. In: Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025. (pp. pp. 212-221). IEEE: Tucson, AZ, USA. Green open access

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Abstract

Preserving boundary continuity in the translation of 360-degree panoramas remains a significant challenge for existing text-driven image-to-image translation methods. These methods often produce visually jarring discontinuities at the translated panorama's boundaries, disrupting the immersive experience. To address this issue, we propose 360PanT, a training-free approach to text-based 360-degree panorama-to-panorama translation with boundary continuity. Our 360PanT achieves seamless translations through two key components: boundary continuity encoding and seamless tiling translation with spatial control. Firstly, the boundary continuity encoding embeds critical boundary continuity information of the input 360-degree panorama into the noisy latent representation by constructing an extended input image. Secondly, leveraging this embedded noisy latent representation and guided by a target prompt, the seamless tiling translation with spatial control enables the generation of a translated image with identical left and right halves while adhering to the extended input's structure and semantic layout. This process ensures a final translated 360-degree panorama with seamless boundary continuity. Experimental results on both real-world and synthesized datasets demonstrate the effectiveness of our 360PanT in translating 360-degree panoramas. Code is available at https://github.com/littlewhitesea/360PanT.

Type: Proceedings paper
Title: 360PanT: Training-Free Text-Driven 360-Degree Panorama-to-Panorama Translation
Event: 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Dates: 26 Feb 2025 - 6 Mar 2025
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/WACV61041.2025.00031
Publisher version: https://doi.org/10.1109/wacv61041.2025.00031
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Computer vision, Translation, Image coding, Codes, Semantics, Layout, Immersive experience, Encoding, Noise measurement
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10208499
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