  Creating 3D assets from single-view images is a complex task that demands a
deep understanding of the world. Recently, feed-forward 3D generative models
have made significant progress by training large reconstruction models on
extensive 3D datasets, with triplanes being the preferred 3D geometry
representation. However, effectively utilizing the geometric priors of
triplanes, while minimizing artifacts caused by generated inconsistent
multi-view images, remains a challenge. In this work, we present
\textbf{Fre}quency modulat\textbf{e}d tri\textbf{plane} (\textbf{Freeplane}), a
simple yet effective method to improve the generation quality of feed-forward
models without additional training. We first analyze the role of triplanes in
feed-forward methods and find that the inconsistent multi-view images introduce
high-frequency artifacts on triplanes, leading to low-quality 3D meshes. Based
on this observation, we propose strategically filtering triplane features and
combining triplanes before and after filtering to produce high-quality textured
meshes. These techniques incur no additional cost and can be seamlessly
integrated into pre-trained feed-forward models to enhance their robustness
against the inconsistency of generated multi-view images. Both qualitative and
quantitative results demonstrate that our method improves the performance of
feed-forward models by simply modulating triplanes. All you need is to modulate
the triplanes during inference.
