Update README.md

README.md

@@ -61,14 +61,37 @@ After downloading and unzipping everything, the dataset directories should look
 This dataset is derived from multiple source datasets, each governed by its own copyright and licensing terms. All rights and credit remain with the original copyright holders. This derivative dataset is intended for non-commercial research and educational purposes unless otherwise explicitly permitted by the original licenses. Any redistribution or derivative use of any part of this dataset must comply with the respective license terms of the original sources. This dataset is provided “as is” without warranty of any kind. The creators of this dataset expressly disclaim any liability for damages arising from its use.
 By using this dataset, you agree to comply with the terms and conditions set forth by each original data source. In no event shall the creators of this dataset be liable for any misuse, infringement, or violation of the underlying copyrights. 
 
-Please review the specific terms for each component below.
-
+Please review the specific terms for each component below. **If you evaluate on *DepthCues*, you are encouraged to also cite the original papers listed below, as our benchmark is largely derived from these works.**
 
 | Dataset        | Publication | Copyright |
 |----------------|------------|-----------|
-| **Elevation**  | Workman, S., Zhai, M., & Jacobs, N. Horizon lines in the wild. *BMVC 2016.* | [link](https://mvrl.cse.wustl.edu/ack.html) |
+| **Elevation**  | Workman, S., Zhai, M., & Jacobs, N. Horizon lines in the wild. *BMVC 2016.* < | [WashU license link](https://huggingface.co/datasets/danier97/depthcues/blob/main/HLW_LICENSE.txt), [link](https://mvrl.cse.wustl.edu/ack.html) |
 | **Light-shadow** | Wang, T., Hu, X., Wang, Q., Heng, P. A., & Fu, C. W. Instance shadow detection. *CVPR 2020.* | [link](https://github.com/stevewongv/InstanceShadowDetection/blob/master/LICENSE) |
 | **Occlusion** | Zhu, Y., Tian, Y., Metaxas, D., & Dollár, P. Semantic amodal segmentation. *CVPR 2017.*  <br> Lin, T. Y., et al. Microsoft COCO: Common objects in context. *ECCV 2014.* <br> Arbelaez, P., et al. Contour detection and hierarchical image segmentation. *T-PAMI 2010.* | [COCO-A link](https://arxiv.org/abs/1509.01329), [COCO link](https://cocodataset.org/#termsofuse), [BSDS link](https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/resources.html) |
 | **Perspective** | Zhou, Z., Farhat, F., & Wang, J. Z. Detecting dominant vanishing points in natural scenes with application to composition-sensitive image retrieval. *IEEE T-MM 2017.* | [AVA link](https://arxiv.org/abs/1705.08421), [Flickr link](https://www.flickr.com/creativecommons/) |
 | **Size** | Geiger, A., Lenz, P., & Urtasun, R. Are we ready for autonomous driving? The KITTI vision benchmark suite. *CVPR 2012.* <br> Song, S., Lichtenberg, S. P., & Xiao, J. SUN RGB-D: A RGB-D scene understanding benchmark suite. *CVPR 2015.* | [KITTI link](https://www.cvlibs.net/datasets/kitti/), [SUN-RGBD link](https://rgbd.cs.princeton.edu/challenge.html) |
-| **Texture-grad** | Cimpoi, M., Maji, S., Kokkinos, I., Mohamed, S., & Vedaldi, A. Describing textures in the wild. *CVPR 2014.* | [link](https://www.robots.ox.ac.uk/~vgg/data/dtd/index.html) |
+| **Texture-grad** | Cimpoi, M., Maji, S., Kokkinos, I., Mohamed, S., & Vedaldi, A. Describing textures in the wild. *CVPR 2014.* | [link](https://www.robots.ox.ac.uk/~vgg/data/dtd/index.html) |
+
+# Citation
+If you find benchmark useful, please cite our paper:
+```
+@article{danier2024depthcues,
+    title = {DepthCues: Evaluating Monocular Depth Perception in Large Vision Models},
+    author = {Danier, Duolikun and Aygün, Mehmet and Li, Changjian and Bilen, Hakan and Mac Aodha, Oisin},
+    journal = {CVPR},
+    year = {2025},
+}
+```
+
+If you evaluate on our benchmark, you are encouraged to also cite the original papers that proposed the source datasets of *DepthCues*:
+```
+[1] Workman, S., Zhai, M., & Jacobs, N. Horizon lines in the wild. BMVC 2016.
+[2] Wang, T., Hu, X., Wang, Q., Heng, P. A., & Fu, C. W. Instance shadow detection. CVPR 2020.
+[3] Zhu, Y., Tian, Y., Metaxas, D., & Dollár, P. Semantic amodal segmentation. CVPR 2017.
+[4] Lin, T. Y., et al. Microsoft COCO: Common objects in context. ECCV 2014. 
+[5] Arbelaez, P., et al. Contour detection and hierarchical image segmentation. T-PAMI 2010.
+[6] Zhou, Z., Farhat, F., & Wang, J. Z. Detecting dominant vanishing points in natural scenes with application to composition-sensitive image retrieval. IEEE T-MM 2017.
+[7] Geiger, A., Lenz, P., & Urtasun, R. Are we ready for autonomous driving? The KITTI vision benchmark suite. CVPR 2012.
+[8] Song, S., Lichtenberg, S. P., & Xiao, J. SUN RGB-D: A RGB-D scene understanding benchmark suite. CVPR 2015.
+[9] Cimpoi, M., Maji, S., Kokkinos, I., Mohamed, S., & Vedaldi, A. Describing textures in the wild. CVPR 2014.
+```