Update README.md

README.md

@@ -1,5 +1,4 @@
 ---
-license: openrail
 language:
 - en
 tags:
@@ -8,29 +7,24 @@ tags:
 ---
 # Dataset Card for Dataset Name
 
-Omnicount-191 is a dataset that caters to a broad spectrum of visual categories and instances featuring various visual categories with multiple instances and classes per image. The current datasets, primarily designed for object counting, focusing on singular object categories like humans and vehicles, fall short for multi-label object counting tasks. Despite the presence of multi-class datasets like MS COCO their utility is limited for counting due to the sparse nature of object appearance. Addressing this gap, we created a new dataset with 30,230 images spanning 191 diverse categories, including kitchen utensils, office supplies, vehicles, and animals. This dataset, featuring a wide range of object instance counts per image ranging from 1 to 160 and an average count of 10, bridges the existing void and establishes a benchmark for assessing counting models in varied scenarios.
-
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
+OmniCount-191 is a first-of-its-kind dataset with multi-label object counts, including points, bounding boxes, and VQA annotations. 
 
 ## Dataset Details
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
+Omnicount-191 is a dataset that caters to a broad spectrum of visual categories and instances featuring various visual categories with multiple instances and classes per image. The current datasets, primarily designed for object counting, focusing on singular object categories like humans and vehicles, fall short for multi-label object counting tasks. Despite the presence of multi-class datasets like MS COCO their utility is limited for counting due to the sparse nature of object appearance. Addressing this gap, we created a new dataset with 30,230 images spanning 191 diverse categories, including kitchen utensils, office supplies, vehicles, and animals. This dataset, featuring a wide range of object instance counts per image ranging from 1 to 160 and an average count of 10, bridges the existing void and establishes a benchmark for assessing counting models in varied scenarios.
 
 
 
-- **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
+- **Curated by:** [Anindya Mondal](https://mondalanindya.github.io), [Sauradip Nag](http://sauradip.github.io/), [Xiatian Zhu](https://surrey-uplab.github.io), [Anjan Dutta](https://www.surrey.ac.uk/people/anjan-dutta)
+- **License:** [OpenRAIL]
 
-### Dataset Sources [optional]
+### Dataset Sources
 
-<!-- Provide the basic links for the dataset. -->
+**To be added soon**
 
-- **Repository:** [More Information Needed]
+- **Repository:** []
 - **Paper [optional]:** [More Information Needed]
 - **Demo [optional]:** [More Information Needed]
 
@@ -120,11 +114,17 @@ Users should be made aware of the risks, biases and limitations of the dataset.
 
 **BibTeX:**
 
-[More Information Needed]
+```
+
+@article{mondal2024omnicount,
+  title={OmniCount: Multi-label Object Counting with Semantic-Geometric Priors},
+  author={Mondal, Anindya and Nag, Sauradip and Zhu, Xiatian and Dutta, Anjan},
+  journal={arXiv preprint arXiv:2403.05435},
+  year={2024}
+}
+```
 
-**APA:**
 
-[More Information Needed]
 
 ## Glossary [optional]
 
@@ -136,9 +136,9 @@ Users should be made aware of the risks, biases and limitations of the dataset.
 
 [More Information Needed]
 
-## Dataset Card Authors [optional]
+## Dataset Card Authors
 
-[More Information Needed]
+[Anindya Mondal](https://mondalanindya.github.io), [Sauradip Nag](http://sauradip.github.io/), [Xiatian Zhu](https://surrey-uplab.github.io), [Anjan Dutta](https://www.surrey.ac.uk/people/anjan-dutta)
 
 ## Dataset Card Contact