PixelSynth: Generating a 3D-Consistent Experience From a Single Image

Chris Rockwell, David F. Fouhey, Justin Johnson; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, pp. 14104-14113

Abstract

Recent advancements in differentiable rendering and 3D reasoning have driven exciting results in novel view synthesis from a single image. Despite realistic results, methods are limited to relatively small view change. In order to synthesize immersive scenes, models must also be able to extrapolate. We present an approach that fuses 3D reasoning with autoregressive modeling to outpaint large view changes in a 3D-consistent manner, which enables scene synthesis. We demonstrate considerable improvement in single-image large-angle view synthesis results compared to a variety of methods and possible variants across simulated and real datasets. In addition, we show increased 3D consistency compared to alternative accumulation methods.

Related Material

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[bibtex]
@InProceedings{Rockwell_2021_ICCV, author = {Rockwell, Chris and Fouhey, David F. and Johnson, Justin}, title = {PixelSynth: Generating a 3D-Consistent Experience From a Single Image}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2021}, pages = {14104-14113} }