From 470cfc4a77e69268a010e14bcb5c858cfe657d38 Mon Sep 17 00:00:00 2001 From: Xun Huang Date: Thu, 25 Jul 2019 11:48:56 -0700 Subject: [PATCH] Update README.md --- README.md | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 1aef05d..21135f9 100644 --- a/README.md +++ b/README.md @@ -3,13 +3,16 @@ This repository contains a PyTorch implementation of the paper: [PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flows](https://arxiv.org/abs/1906.12320). - +
[Guandao Yang*](http://www.guandaoyang.com), [Xun Huang*](http://www.cs.cornell.edu/~xhuang/), [Zekun Hao](http://www.cs.cornell.edu/~zekun/), [Ming-Yu Liu](http://mingyuliu.net/), [Serge Belongie](http://blogs.cornell.edu/techfaculty/serge-belongie/), [Bharath Hariharan](http://home.bharathh.info/) +(* equal contribution) +
+ICCV 2019 (**Oral**) ## Introduction @@ -27,7 +30,7 @@ As 3D point clouds become the representation of choice for multiple vision and g * G++ or GCC 5. * [PyTorch](http://pytorch.org/). Codes are tested with version 1.0.1 * [torchdiffeq](https://github.com/rtqichen/torchdiffeq). -* (Optional) [Tensorboard](https://www.tensorflow.org/) for visualization of training process. +* (Optional) [Tensorboard](https://www.tensorflow.org/) for visualization of the training process. Following is the suggested way to install these dependencies: ```bash @@ -53,7 +56,7 @@ cd data unzip ShapeNetCore.v2.PC15k.zip ``` -Please contact us if you need point clouds for ModelNet dataset. +Please contact us if you need point clouds for the ModelNet dataset. ## Training @@ -71,7 +74,7 @@ Example training scripts can be found in `scripts/` folder. ## Pre-trained models and test Pretrained models can be downloaded from this [link](https://drive.google.com/file/d/1dcxjuuKiAXZxhiyWD_o_7Owx8Y3FbRHG/view?usp=sharing). -Following is the suggested way to evaluate the performance of the pre-trained models. +The following is the suggested way to evaluate the performance of the pre-trained models. ```bash unzip pretrained_models.zip; # This will create a folder named pretrained_models @@ -87,7 +90,7 @@ CUDA_VISIBLE_DEVICES=0 ./scripts/shapenet_airplane_gen_test.sh ## Demo -The demo relies on [Open3D](http://www.open3d.org/). Following is the suggested way to install it: +The demo relies on [Open3D](http://www.open3d.org/). The following is the suggested way to install it: ```bash conda install -c open3d-admin open3d ```