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adminslack

autocuts

basicdeformationapp

A basic deformation tool with two viewports based on libigl

common-3d-test-models

Repository containing common 3D test models in original format with original source if known

compmajor

An implementation of "Geometric optimization via composite majorization" [Shtengel et al. 2017]

deep-box-packing

The Packing problem has gained much relevance with the recent upheaval of the delivery and retail industry. Companies all over the world are now subject to massive logistics & operations schemes, and their warehouses‘ e ectiveness is irrevocably bound to how well their products are packed into trucks for distribution. Optimizing this process may lead to huge improvements in performance, time use, resource management and to ultimately increasing profits. Seeking to perform and deliver this optimization, this work proposes a new method called “Deep Box Packing” (DBP), an online system which is able to provide an optimized packing strategy for an arbitrary set of three-dimensional boxes arriving in real-time. DBP was trained using Deep Reinforcement Learning and leverages the power of attention mechanisms in a modified version of the Transformer Network called here the Mapping Transformer. It was conceived to work under partial information, in real-time, and to respond to all of the three inherent questions of packing: which box to take (selection), where to place it in the container (position) and how to place it (orientation) at every given moment in time. Its reward function was tailored not only in terms of optimizing the final Volume utilization of the container but also in terms of the feasibility of the packing sequence, withholding constraints such as box stability and accessibility to the packing positions from the entrance of the container. Under this scenario, DBP was capable of achieving outstanding results in the tested instances up to 100% volume utilization in fully feasible packings. Under comparative tests, DBP considerably improved results obtained from a wall-building LB-Greedy heuristic and showed high generalization capacity to different sizes of the Information window (number of boxes from the whole sequence it can see and choose from at any moment in time). After a set of visual step-by-step analyses of DBP’s behavior in generated packing sequences, it was also shown that it was able to achieve high geometric understanding and great potential for being expanded into a real warehouse scenario.

hessianik

Source code for the paper "Inverse Kinematics Problems with Exact Hessian Matrices" at Motion in Games (MIG) 2017

https---github.com-haifagraphics-diffprocsdf

imguizmo

Immediate mode 3D gizmo for scene editing and other controls based on Dear Imgui

libigl

Simple C++ geometry processing library.

libigl_params

libigl version for autocuts only

matlabik

matlabinteractivesolver

A template for an interactive, asynchronous solver with GUI in Matlab

pardisosolver

a small wrapper for pardiso with libigl and Eigen

roipo.github.io

simplehydrology

Procedural Hydrology / River / Lake Simulation

starter-hugo-academic

🎓 创建一个学术网站. Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify.

wowchemy-hugo-modules

🔥 The website builder for Hugo. No code, build with widgets! 创建在线课程，学术简历或初创网站。