Sharp Monocular View Synthesis in Less Than a Second
Lars Mescheder, Wei Dong, Shiwei Li, Xuyang BAI, Marcel Santos, Peiyun Hu, Bruno Lecouat, Mingmin Zhen
Abstract
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.
BibTeX
@inproceedings{
mescheder2026sharp,
title={Sharp Monocular View Synthesis in Less Than a Second},
author={Lars Mescheder and Wei Dong and Shiwei Li and Xuyang BAI and Marcel Santos and Peiyun Hu and Bruno Lecouat and Mingmin Zhen and Ama{\"e}l Delaunoy and Tian Fang and Yanghai Tsin and Stephan Richter and Vladlen Koltun},
booktitle={The Fourteenth International Conference on Learning Representations},
year={2026},
url={https://openreview.net/forum?id=yx3g4sF70y}
}