From 9e91cc2b8099e53fdaccd56e62a8aa0019a64494 Mon Sep 17 00:00:00 2001 From: Xu Ma Date: Thu, 3 Feb 2022 20:08:27 -0500 Subject: [PATCH] Update README.md --- README.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 6fe9cc0..528ac16 100644 --- a/README.md +++ b/README.md @@ -6,10 +6,7 @@ __Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/rethinking-network-design-and-local-geometry/3d-point-cloud-classification-on-scanobjectnn)](https://paperswithcode.com/sota/3d-point-cloud-classification-on-scanobjectnn?p=rethinking-network-design-and-local-geometry) [archived: Feb/3/2022] -## TO DO: -- [ ] release paper/codes by Feb/7/2022 -- [ ] update std bug (unstable testing) -- [ ] project page +
@@ -17,6 +14,11 @@ __Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual Overview of one stage in PointMLP. Given an input point cloud, PointMLP progressively extract local features using residual point MLP blocks. In each stage, we first transform local point using a geometric affine module, then local points are are extracted before and after aggregation respectively. By repeating multiple stages, PointMLP progressively enlarge the receptive field and model entire point cloud geometric information. +## TO DO: +- [ ] release paper/codes by Feb/7/2022 +- [ ] update std bug (unstable testing) +- [ ] project page + ## Updates Jan/31/2022: We will release an official code here: [PointMLP-pytorch](https://github.com/13952522076/pointMLP-pytorch)