Asset Details
Do you wish to reserve the book?
Mesh Silksong: Auto-Regressive Mesh Generation as Weaving Silk
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Mesh Silksong: Auto-Regressive Mesh Generation as Weaving Silk
Do you wish to request the book?
Mesh Silksong: Auto-Regressive Mesh Generation as Weaving Silk
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Paper
Mesh Silksong: Auto-Regressive Mesh Generation as Weaving Silk
2025
Overview
We introduce Mesh Silksong, a compact and efficient mesh representation tailored to generate the polygon mesh in an auto-regressive manner akin to silk weaving. Existing mesh tokenization methods always produce token sequences with repeated vertex tokens, wasting the network capability. Therefore, our approach tokenizes mesh vertices by accessing each mesh vertice only once, reduces the token sequence's redundancy by 50\\%, and achieves a state-of-the-art compression rate of approximately 22\\%. Furthermore, Mesh Silksong produces polygon meshes with superior geometric properties, including manifold topology, watertight detection, and consistent face normals, which are critical for practical applications. Experimental results demonstrate the effectiveness of our approach, showcasing not only intricate mesh generation but also significantly improved geometric integrity.
Publisher
Cornell University Library, arXiv.org
Subject
