pvnieo / dpfm Goto Github PK
View Code? Open in Web Editor NEWPytorch code for "DPFM: Deep Partial Functional Maps" - 3DV 2021 (Oral)
Home Page: https://arxiv.org/abs/2110.09994
License: GNU General Public License v3.0
Pytorch code for "DPFM: Deep Partial Functional Maps" - 3DV 2021 (Oral)
Home Page: https://arxiv.org/abs/2110.09994
License: GNU General Public License v3.0
Hello, is there any chance you can release the pre-trained models on cp2p?
There are the pre-trained models for shrec-cuts and shrec-holes, which is awesome!
Also, can you release the ground truth maps for test set of cp2p?
Your evaluation code needs them, and it would be great to have to compute the error on the test set.
Thank you,
Luca
Hello, I am reading this paper recently, and I am very interested in the method of DPFM. I would like to know when the code can be released.
thank you
Hi, I have read your paper and viewed your codes. I want to know after getting the functional map between shape A and B, how can I use the it to transform the shape A to B? Is there any possible to convert the functional map to the point-to-point correspondence? I see the C_gt is generated by using the points correspondence map from the training dataset, however, if we only have the functional map, how can I recover the points correspondence map?
Hello, I have read your paper recently and am very interested in your work. Will the code be released before December 1st this year? This will be of great help to my work!
thanks
Excuse me, I'm here to trouble you again. I think you have already released part of the code. When will the other codes be released?
Where can I get the datasets I need for training?
Can you provide the download link of the dataset?
Thx!!
Hi, Happy New Year!!!
I have a question about the use of Shrec'16 Dataset.
I download the Dataset here: https://www.dais.unive.it/~shrec2016/dataset.php
There are three contents available for download, and I downloaded the first one:
Partial datasets with ground truth correspondences (~200 shapes)
Test code to load and show ground-truth maps between shapes
The evaluation cuts (200 shapes) and holes (200 shapes) databases
I don't know if I downloaded it correctly.
When I unzip the downloaded file, I found it has three folders, "cuts", "holes", "null", and the label correspondence files is ".baryc_gt" as suffix.
In the documentation I found the following description:
Ground-truth is provided for each deformed shape as a ASCII file with baryc_gt (baryc_gt_sym for the symmetric ground-truth) extension. Each row contains the triangle index and the barycentric weight of the corresponding point of the relative shape in canonical pose.
However, in the code implementation such as "shrec_partial_dataset.py", and the implementation of the "ShrecPartialDataset" class, i found the label correspondence, and the code about read ground truth file is something about the file which is ".map" as suffix, this is different from the label file in Shrec'16 I downloaded.
My question is how do I convert files from '.baryc_gt' to '.map' ?
Thank you for your reply and help, have a nice day~~~
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.