Datasets:

Aleksandar
/

PartEdit-Bench

@@ -61,7 +61,8 @@ tags:
 - Editing
 size_categories:
 - n<1K
-arxiv: 2502.04050
 ---
 # Dataset Card for Dataset Name
@@ -93,53 +94,53 @@ Small benchmark of part editin.
 - **Paper [optional]:** https://arxiv.org/abs/2502.04050
 - **Demo [optional]:** https://partedit.github.io/PartEdit/
-## Uses
 <!-- Address questions around how the dataset is intended to be used. -->
-### Direct Use
 <!-- This section describes suitable use cases for the dataset. -->
-[More Information Needed]
-### Out-of-Scope Use
 <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-[More Information Needed]
-## Dataset Structure
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-[More Information Needed]
-## Dataset Creation
-### Curation Rationale
 <!-- Motivation for the creation of this dataset. -->
-[More Information Needed]
-### Source Data
 <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-#### Data Collection and Processing
 <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-[More Information Needed]
-#### Who are the source data producers?
 <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-[More Information Needed]
-### Annotations [optional]
 <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
@@ -149,17 +150,17 @@ Small benchmark of part editin.
 Using https://www.makesense.ai/ to annotate ground truth regions.
-#### Who are the annotators?
 <!-- This section describes the people or systems who created the annotations. -->
-Annotated GT regions by authors.
-#### Personal and Sensitive Information
 <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-There are no personal identifiers, other than images of generated (synth) and few real samples.
 ## Bias, Risks, and Limitations
@@ -178,7 +179,7 @@ Users should be made aware of the risks, biases and limitations of the dataset.
 <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 **BibTeX:**
 @misc{cvejic2025parteditfinegrainedimageediting,
       title={PartEdit: Fine-Grained Image Editing using Pre-Trained Diffusion Models},
       author={Aleksandar Cvejic and Abdelrahman Eldesokey and Peter Wonka},
@@ -188,25 +189,25 @@ Users should be made aware of the risks, biases and limitations of the dataset.
       primaryClass={cs.CV},
       url={https://arxiv.org/abs/2502.04050},
 }
 **APA:**
 Cvejic, A., Eldesokey, A., & Wonka, P. (2025). PartEdit: Fine-Grained Image Editing using Pre-Trained Diffusion Models. arXiv preprint arXiv:2502.04050.
-## Glossary [optional]
 <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Dataset Card Authors [optional]
-[More Information Needed]
-## Dataset Card Contact
-First author.

 - Editing
 size_categories:
 - n<1K
+arxiv: 2502.0405
+pretty_name: PartEdit
 ---
 # Dataset Card for Dataset Name
 - **Paper [optional]:** https://arxiv.org/abs/2502.04050
 - **Demo [optional]:** https://partedit.github.io/PartEdit/
+<!-- ## Uses -->
 <!-- Address questions around how the dataset is intended to be used. -->
+<!-- ### Direct Use -->
 <!-- This section describes suitable use cases for the dataset. -->
+<!-- [More Information Needed] -->
+<!-- ### Out-of-Scope Use -->
 <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
+<!-- [More Information Needed] -->
+<!-- ## Dataset Structure -->
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+<!-- [More Information Needed] -->
+<!-- ## Dataset Creation -->
+<!-- ### Curation Rationale -->
 <!-- Motivation for the creation of this dataset. -->
+<!-- [More Information Needed] -->
+<!-- ### Source Data -->
 <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
+<!-- #### Data Collection and Processing -->
 <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
+<!-- [More Information Needed] -->
+<!-- #### Who are the source data producers? -->
 <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
+<!-- [More Information Needed] -->
+<!-- ### Annotations [optional] -->
 <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
 Using https://www.makesense.ai/ to annotate ground truth regions.
+<!-- #### Who are the annotators? -->
 <!-- This section describes the people or systems who created the annotations. -->
+<!-- Annotated GT regions by authors. -->
+<!-- #### Personal and Sensitive Information -->
 <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
+<!-- There are no personal identifiers, other than images of generated (synth) and few real samples.  -->
 ## Bias, Risks, and Limitations
 <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
 **BibTeX:**
+```
 @misc{cvejic2025parteditfinegrainedimageediting,
       title={PartEdit: Fine-Grained Image Editing using Pre-Trained Diffusion Models},
       author={Aleksandar Cvejic and Abdelrahman Eldesokey and Peter Wonka},
       primaryClass={cs.CV},
       url={https://arxiv.org/abs/2502.04050},
 }
+```
 **APA:**
+```
 Cvejic, A., Eldesokey, A., & Wonka, P. (2025). PartEdit: Fine-Grained Image Editing using Pre-Trained Diffusion Models. arXiv preprint arXiv:2502.04050.
+```
+<!-- ## Glossary [optional] -->
 <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
+<!-- [More Information Needed] -->
+<!-- ## More Information [optional] -->
+<!-- [More Information Needed] -->
+<!-- ## Dataset Card Authors [optional] -->
+<!-- [More Information Needed] -->
+<!-- ## Dataset Card Contact -->
+<!-- First author. -->