Engstler_SynCity_Training-Free_Generation_of_3D_Worlds@ICCV2025@CVF

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#1 SynCity: Training-Free Generation of 3D Worlds [PDF] [Copy] [Kimi] [REL]

Authors: Paul Engstler, Aleksandar Shtedritski, Iro Laina, Christian Rupprecht, Andrea Vedaldi

We propose SynCity, a method for generating explorable 3D worlds from textual descriptions. Our approach leverages pre-trained textual, image, and 3D generators without requiring fine-tuning or inference-time optimization. While most 3D generators are object-centric and unable to create large-scale worlds, we demonstrate how 2D and 3D generators can be combined to produce ever-expanding scenes. The world is generated tile by tile, with each new tile created within its context and seamlessly integrated into the scene. SynCity enables fine-grained control over the appearance and layout of the generated worlds, which are both detailed and diverse.

Subject: ICCV.2025 - Poster