Update README.md

README.md

@@ -45,13 +45,32 @@ Since the number of images is large (roughly 899K), we store and provide the ima
 | `key`   | str    | A unique identifier for each data entry in the dataset. |
 | `url`   | str    | The URL path to the image stored in the dataset repository on HuggingFace. All URLs point to the base HuggingFace repository where images are stored. |
 | `jpg`   | image  | The image data associated with each entry, displayed as a thumbnail in the dataset viewer. This column stores the actual image content relevant to the conversation in the dataset. |
-| `json`  | dict   | Contains additional metadata and information for each image, structured as a dictionary. The JSON field typically includes the following keys: `image_source`, `image_url`, `index`. |
+| `json`  | dict   | Contains additional metadata and information for each image, structured as a dictionary. The JSON field typically includes the following keys: `image_source`, `image_url`, `face_description`, and `index`. |
 
-- **`image_source`**: Source of the image (`p-t2i`), where:
-  - `"p-t2i"`: Image from a general text-to-image generative model (i.e., [SDXL-Lightning](https://huggingface.co/ByteDance/SDXL-Lightning)).
+- **`image_source`**: Source of the image (`t2i`), where:
+  - `"t2i"`: Image from a general text-to-image generative model (i.e., [SDXL-Lightning](https://huggingface.co/ByteDance/SDXL-Lightning)).
 - **`image_url`**: External URL where the image was originally sourced. In this dataset, the `image_url` is always an empty string.
+- **`face_description`**: The virtual human face description that is created based on a predefined human attribute collection from [CosmicMan](https://openaccess.thecvf.com/content/CVPR2024/papers/Li_CosmicMan_A_Text-to-Image_Foundation_Model_for_Humans_CVPR_2024_paper.pdf).
 - **`index`**: A unique index identifier for each image within the dataset, which is the same as the `key` field.
 
+### Data Instance
+
+The following is an example instance from the dataset.
+
+```json
+{
+  "__key__": "14c9849f-ec2b-4b96-9dae-71645106c8ab",
+  "__url__": "hf://datasets/passing2961/stark-face-image@c3a0b98979522e79174676583528c3c2f54741a8/stark-train-000000-of-000002.tar",
+  "jpg": "<image/png>",
+  "json": {
+    "face_description": "A nearly full-body shot, a 85-years-old female from Japan, fit, a brown wall, ponytail blonde above chest hair, off-shoulder short scoop neckline sleeveless silk graphic dress, striped green scoop neckline normal sleeveless cotton graphic camisole, cotton graphic tie.",
+    "image_source": "t2i",
+    "image_url": "",
+    "index": "14c9849f-ec2b-4b96-9dae-71645106c8ab"
+  }
+}
+```
+
 ## Dataset Construction
 
 We construct the **Stark** dataset using our proposed novel framework, MCU, which distills long-term multi-modal dialogue from ChatGPT and our proposed Plan-and-Execute Image Aligner, powered by a personalized text-to-image generative model (i.e., PhotoMaker), image database retrieval, and web search. All prompt templates used for dataset construction are presented in the Appendix of our paper.
@@ -76,3 +95,11 @@ This work was supported by a grant from the KAIST-KT joint research project thro
 
 If you find the resources in this repository useful, please cite our work:
 
+```
+@article{lee2024stark,
+  title={Stark: Social Long-Term Multi-Modal Conversation with Persona Commonsense Knowledge},
+  author={Lee, Young-Jun and Lee, Dokyong and Youn, Junyoung and Oh, Kyeongjin and Ko, Byungsoo and Hyeon, Jonghwan and Choi, Ho-Jin},
+  journal={arXiv preprint arXiv:2407.03958},
+  year={2024}
+}
+```