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created at

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InfiniteNature-Zero

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site name

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2025-12-15 09:00:22

raw text

InfiniteNatureZero InfiniteNature- Zero Learning Perpetual View Generation of Natural Scenes from Single Images Zhengqi Li 1 , Qianqian Wang 1,2 , Noah Snavely 1 , Angjoo Kanazawa 3 , 1 Google Research   2 Cornell Tech, Cornell University   3 UC Berkeley ECCV 2022 (Oral Presentation) Paper arXiv Video Supp Code Training only on collections of single photo, we learn perpetual view generation from a input RGB image Abstract We present a method for learning to generate unbounded flythrough videos of natural scenes starting from a single view, where this capability is learned from a collection of single photographs, without requiring camera poses or even multiple views of each scene. To achieve this, we propose a novel self-supervised view generation training paradigm, where we sample and rendering virtual camera trajectories, including cyclic ones, allowing our model to learn stable view generation from a collection o...

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