CubeComposer: Spatio-Temporal Autoregressive 4K 360° Video Generation from Perspective Video
Generating high-quality 360° panoramic videos from perspective input is one of the crucial applications for virtual reality (VR), whereby high-resolution videos are especially important for immersive experience. Existing methods are constrained by computational limitations of vanilla diffusion models, only supporting leq 1K resolution native generation and relying on suboptimal post super-resolution to increase resolution. We introduce CubeComposer, a novel spatio-temporal autoregressive diffusion model that natively generates 4K-resolution 360° videos. By decomposing videos into cubemap representations with six faces, CubeComposer autoregressively synthesizes content in a well-planned spatio-temporal order, reducing memory demands while enabling high-resolution output. Specifically, to address challenges in multi-dimensional autoregression, we propose: (1) a spatio-temporal autoregressive strategy that orchestrates 360° video generation across cube faces and time windows for coherent synthesis; (2) a cube face context management mechanism, equipped with a sparse context attention design to improve efficiency; and (3) continuity-aware techniques, including cube-aware positional encoding, padding, and blending to eliminate boundary seams. Extensive experiments on benchmark datasets demonstrate that CubeComposer outperforms state-of-the-art methods in native resolution and visual quality, supporting practical VR application scenarios. Project page: https://lg-li.github.io/project/cubecomposer
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Lingen Li
claimed_verified
2026-03-05T10:02:05.557Z
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/avatars/b16385eaa612578728e2c6460a76b38f.svg
Lingen Li
l-li
user
l-li
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Guangzhi Wang
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Xiaoyu Li
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Zhaoyang Zhang
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Qi Dou
69a9011b8b5b27c7ea9fa68b
Jinwei Gu
69a9011b8b5b27c7ea9fa68c
Tianfan Xue
admin_assigned
2026-03-05T10:29:54.796Z
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https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/5VrG0IZjYrDLiatOr4y06.png
Tianfan Xue
littlemouse9
user
littlemouse9
69a9011b8b5b27c7ea9fa68d
Ying Shan
CubeComposer: Spatio-Temporal Autoregressive 4K 360° Video Generation from Perspective Video
Generating high-quality 360° panoramic videos from perspective input is one of the crucial applications for virtual reality (VR), whereby high-resolution videos are especially important for immersive experience. Existing methods are constrained by computational limitations of vanilla diffusion models, only supporting leq 1K resolution native generation and relying on suboptimal post super-resolution to increase resolution. We introduce CubeComposer, a novel spatio-temporal autoregressive diffusion model that natively generates 4K-resolution 360° videos. By decomposing videos into cubemap representations with six faces, CubeComposer autoregressively synthesizes content in a well-planned spatio-temporal order, reducing memory demands while enabling high-resolution output. Specifically, to address challenges in multi-dimensional autoregression, we propose: (1) a spatio-temporal autoregressive strategy that orchestrates 360° video generation across cube faces and time windows for coherent synthesis; (2) a cube face context management mechanism, equipped with a sparse context attention design to improve efficiency; and (3) continuity-aware techniques, including cube-aware positional encoding, padding, and blending to eliminate boundary seams. Extensive experiments on benchmark datasets demonstrate that CubeComposer outperforms state-of-the-art methods in native resolution and visual quality, supporting practical VR application scenarios. Project page: https://lg-li.github.io/project/cubecomposer
CubeComposer is a spatio-temporal autoregressive diffusion model that generates high-resolution 360° panoramic videos by decomposing them into cubemap representations and using efficient autoregressive synthesis techniques.
spatio-temporal autoregressive diffusion model cubemap representations autoregressive synthesis sparse context attention cube-aware positional encoding padding blending boundary seams