Sharp Monocular View Synthesis in Less Than a Second
We present SHARP, an approach to photorealistic view synthesis from a single image. Given a single photograph, SHARP regresses the parameters of a 3D Gaussian representation of the depicted scene. This is done in less than a second on a standard GPU via a single feedforward pass through a neural network. The 3D Gaussian representation produced by SHARP can then be rendered in real time, yielding high-resolution photorealistic images for nearby views. The representation is metric, with absolute scale, supporting metric camera movements. Experimental results demonstrate that SHARP delivers robust zero-shot generalization across datasets. It sets a new state of the art on multiple datasets, reducing LPIPS by 25-34% and DISTS by 21-43% versus the best prior model, while lowering the synthesis time by three orders of magnitude. Code and weights are provided at https://github.com/apple/ml-sharp
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Lars Mescheder
claimed_verified
2025-12-18T08:00:35.461Z
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Lars Mescheder
LarsMescheder
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LarsMescheder
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Wei Dong
claimed_verified
2025-12-15T08:13:57.186Z
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Wei Dong
theNded
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theNded
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Shiwei Li
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Xuyang Bai
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Marcel Santos
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Peiyun Hu
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Bruno Lecouat
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Mingmin Zhen
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Amaël Delaunoy
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2025-12-15T08:13:55.323Z
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Amael Delaunoy
amael-apple
user
amael-apple
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Tian Fang
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Yanghai Tsin
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Stephan R. Richter
693be2e99874a2a5e4ffb43a
Vladlen Koltun
Sharp Monocular View Synthesis in Less Than a Second
We present SHARP, an approach to photorealistic view synthesis from a single image. Given a single photograph, SHARP regresses the parameters of a 3D Gaussian representation of the depicted scene. This is done in less than a second on a standard GPU via a single feedforward pass through a neural network. The 3D Gaussian representation produced by SHARP can then be rendered in real time, yielding high-resolution photorealistic images for nearby views. The representation is metric, with absolute scale, supporting metric camera movements. Experimental results demonstrate that SHARP delivers robust zero-shot generalization across datasets. It sets a new state of the art on multiple datasets, reducing LPIPS by 25-34% and DISTS by 21-43% versus the best prior model, while lowering the synthesis time by three orders of magnitude. Code and weights are provided at https://github.com/apple/ml-sharp
SHARP synthesizes photorealistic views from a single image using a 3D Gaussian representation, achieving state-of-the-art results with rapid processing.
photorealistic view synthesis 3D Gaussian representation neural network feedforward pass real-time rendering metric representation zero-shot generalization LPIPS DISTS