updated all urls to HKUST server

Author: JunweiLiang

README.md

@@ -4,18 +4,18 @@ This repository contains the code and models for the following paper:
 
 
 **[Peeking into the Future: Predicting Future Person Activities and Locations in Videos](https://arxiv.org/abs/1902.03748)** \
-[Junwei Liang](https://www.cs.cmu.edu/~junweil/),
+[Junwei Liang](https://junweiliang.me/),
 [Lu Jiang](http://www.lujiang.info/),
 [Juan Carlos Niebles](http://www.niebles.net/),
 [Alexander Hauptmann](https://www.cs.cmu.edu/~alex/),
 [Li Fei-Fei](http://vision.stanford.edu/feifeili/) \
 [CVPR 2019](http://cvpr2019.thecvf.com/)
 
-You can find more information at our [Project Page](https://next.cs.cmu.edu/).\
+You can find more information at our [Project Page](https://precognition.team/next).\
 *Please note that this is not an officially supported Google product.*
 
 + *[11/2022] CMU server is down. You can replace all `https://next.cs.cmu.edu` with `https://precognition.team/next/` to download necessary resources.*
-+ *[02/2020] [New paper](https://next.cs.cmu.edu/multiverse/) on multi-future trajectory prediction is accepted by CVPR 2020.*
++ *[02/2020] [New paper](https://precognition.team/next/multiverse/) on multi-future trajectory prediction is accepted by CVPR 2020.*
 
 If you find this code useful in your research then please cite
 

TESTING.md

@@ -2,9 +2,9 @@
 ## Step 1: Prepare the data and model
 We experimented on the [ActEv dataset](https://actev.nist.gov) and the
 [ETH & UCY dataset](https://graphics.cs.ucy.ac.cy/research/downloads/crowd-data).
-The original ActEv annotations can be downloaded from [here](https://next.cs.cmu.edu/data/actev-v1-drop4-yaml.tgz).
+The original ActEv annotations can be downloaded from [here](https://precognition.team/next/data/actev-v1-drop4-yaml.tgz).
 *Please do obtain the data copyright and download the raw videos from their website.*
-You can download our prepared features from the [project page](https://next.cs.cmu.edu)
+You can download our prepared features from the [project page](https://precognition.team/next/)
 by running the script `bash scripts/download_prepared_data.sh`.
 This will download the following data,
 and will require about 31 GB of disk space:

TRAINING.md

@@ -2,9 +2,9 @@
 ## Step 1: Prepare the data and model
 We experimented on the [ActEv dataset](https://actev.nist.gov) and
 the [ETH & UCY dataset](https://graphics.cs.ucy.ac.cy/research/downloads/crowd-data).
-The original ActEv annotations can be downloaded from [here](https://next.cs.cmu.edu/data/actev-v1-drop4-yaml.tgz).
+The original ActEv annotations can be downloaded from [here](https://precognition.team/next/data/actev-v1-drop4-yaml.tgz).
 *Please do obtain the data copyright and download the raw videos from their website.*
-You can download our prepared features from the [project page](next.cs.cmu.edu)
+You can download our prepared features from the [project page](https://precognition.team/next/)
 by running the script `bash scripts/download_prepared_data.sh`.
 This will download the following data, and will require
 about 31 GB of disk space:

scripts/download_prepared_data.sh

@@ -18,9 +18,14 @@
 
 mkdir -p next-data
 
-wget https://next.cs.cmu.edu/data/final_annos.tgz -O next-data/final_annos.tgz
-wget https://next.cs.cmu.edu/data/person_features/actev_personboxfeat.tgz -O next-data/actev_personboxfeat.tgz
-wget https://next.cs.cmu.edu/data/person_features/ethucy_personboxfeat.tgz -O next-data/ethucy_personboxfeat.tgz
+# [02/2023] CMU server is down. Switching to our HKUST (Guangzhou) Precognition lab server
+#wget https://next.cs.cmu.edu/data/final_annos.tgz -O next-data/final_annos.tgz
+#wget https://next.cs.cmu.edu/data/person_features/actev_personboxfeat.tgz -O next-data/actev_personboxfeat.tgz
+#wget https://next.cs.cmu.edu/data/person_features/ethucy_personboxfeat.tgz -O next-data/ethucy_personboxfeat.tgz
+
+wget https://precognition.team/next/data/final_annos.tgz -O next-data/final_annos.tgz
+wget https://precognition.team/next/data/person_features/actev_personboxfeat.tgz -O next-data/actev_personboxfeat.tgz
+wget https://precognition.team/next/data/person_features/ethucy_personboxfeat.tgz -O next-data/ethucy_personboxfeat.tgz
 
 # extract and delete the tar files
 cd next-data

scripts/download_single_models.sh

@@ -18,8 +18,12 @@
 
 mkdir -p next-models
 
-wget https://next.cs.cmu.edu/data/pretrained_models/actev_single_model.tar -O next-models/actev_single_model.tar
-wget https://next.cs.cmu.edu/data/pretrained_models/ethucy_single_model.tar -O next-models/ethucy_single_model.tar
+# [02/2023] CMU server is down. Switching to our HKUST (Guangzhou) Precognition lab server
+#wget https://next.cs.cmu.edu/data/pretrained_models/actev_single_model.tar -O next-models/actev_single_model.tar
+#wget https://next.cs.cmu.edu/data/pretrained_models/ethucy_single_model.tar -O next-models/ethucy_single_model.tar
+
+wget https://precognition.team/next/data/pretrained_models/actev_single_model.tar -O next-models/actev_single_model.tar
+wget https://precognition.team/next/data/pretrained_models/ethucy_single_model.tar -O next-models/ethucy_single_model.tar
 
 # extract and delete the tar files
 cd next-models