updated Readme.md and added LICENSE

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+This license does not apply to the model weights.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

Readme.md

@@ -1,6 +1,8 @@
 # Image Segmentation Using Text and Image Prompts
 This repository contains the code used in the paper ["Image Segmentation Using Text and Image Prompts"](https://arxiv.org/abs/2112.10003).
 
+**The Paper has been accepted to CVPR 2022!**
+
 <img src="overview.png" alt="drawing" height="200em"/>
 
 The systems allows to create segmentation models without training based on:
@@ -41,6 +43,9 @@ git clone https://github.com/juhongm999/hsnet.git
 ```
 
 ### Weights
+
+The MIT license does not apply to these weights.
+
 - [CLIPSeg-D64](https://github.com/timojl/clipseg/raw/master/weights/rd64-uni.pth) (4.1MB, without CLIP weights)
 - [CLIPSeg-D16](https://github.com/timojl/clipseg/raw/master/weights/rd16-uni.pth) (1.1MB, without CLIP weights)
 
@@ -56,12 +61,20 @@ For evaluation use `score.py`. E.g. `python score.py phrasecut.yaml 0 0` will tr
 In order to use the dataset and model wrappers for PFENet, the PFENet repository needs to be cloned to the root folder.
 `git clone https://github.com/Jia-Research-Lab/PFENet.git `
 
+
+### License
+
+The source code files in this repository (excluding model weights) are released under MIT license.
+
 ### Citation
 ```
-@article{lueddecke21
-    title={Image Segmentation Using Text and Image Prompts},
-    author={Timo Lüddecke and Alexander Ecker},
-    journal={arXiv preprint arXiv:2112.10003},
-    year={2021}
+@InProceedings{lueddecke22_cvpr,
+    author    = {L\"uddecke, Timo and Ecker, Alexander},
+    title     = {Image Segmentation Using Text and Image Prompts},
+    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+    month     = {June},
+    year      = {2022},
+    pages     = {7086-7096}
 }
+
 ```