This repo is a third party implementation of the FIGNet Learning Rigid Dynamics with Face Interaction Graph Networks[1], trying to reproduce the results from the original paper. The package also includes the improvement introduced in their following work ( FIGNet* )[2].

2023年2月28日 · 在这里,我们介绍了Face Interaction Graph Network (FigNet),该网从未知的节点到粒子级组合上比已知的节点多4倍,并且比分析仪器所需的最小训练数据提高了8倍。此外,FigNet可以直接从实际数据中学习强力摩擦动态,并可以在少量训练数据下进行更精确的计算工作。

FigNet Core is a simple, scalable, fast, & transport layer-agnostic networking solution for real-time games & apps. Virtually unlimited CCUs - no CCU limit. Easy-to-use with a simple Request-and-response paradigm.

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2022年1月4日 · FigNet Core is a simple, scalable, fast, & transport layer-agnostic networking solution for real-time games & apps. Virtually unlimited CCUs - no CCU limit. Easy-to-use with a simple Request-and-response paradigm. You can run the server as a .NET core app or Unity app. Lightweight & efficient. Highly modular, flexible, and extensible design ...

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A Demo App demonstrating features of FigNet. Contribute to Ahmed310/Agar.FigNet development by creating an account on GitHub.

2022年12月7日 · Here we introduce the Face Interaction Graph Network (FIGNet) which extends beyond GNN-based methods, and computes interactions between mesh faces, rather than nodes. Compared to learned node- and particle-based methods, FIGNet is around 4x more accurate in simulating complex shape interactions, while also 8x more computationally efficient on ...