Omkar2118/datasets huggingface dataset:
TGRDB
Full name: Tour-Guide Robot Dataset and Benchmark

1. Our TGRDB dataset was collected with a 180 fisheye
RGB camera on-board of a moving tour-guide robot. 
2. A first dataset in tour-guide scenario. Statistical comparisons between TGRDB and existing
datasets are refferred to https://arxiv.org/abs/2207.03726.
3. We hope this dataset will drive the progress of research in service robotics, long-term multi-person tracking, and fine-grained or clothes-inconsistency person re-identification.

Introducing paper: TGRMPT: A Head-Shoulder Aided Multi-Person Tracker and a New Large-Scale Dataset for Tour-Guide Robot
OBJ-MDA

The dataset contains images of 16 artworks included in the cultural site “Galleria Regionale di Palazzo Bellomo2”. The collection covers different types of artworks, as well as books, sculptures and paintings. The dataset three domains:
i) synthetic images generated from a 3D model of the cultural site and automatically labeled
during the generation process;
 ii) real images collected by 10 visitors with a HoloLens device and manually labeled;
iii) realimages collected by the same visitors with a GoPro and manually labeled.

Introducing paper: A Multi Camera Unsupervised Domain Adaptation Pipeline for Object Detection in Cultural Sites through Adversarial Learning and Self-Training
CareerCoach 2022

The CareerCoach 2022 gold standard is available for download in the NIF and JSON format, and draws upon documents from a corpus of over 99,000 education courses which have been retrieved from 488 different education providers.

The corpus contains two partitions.:

* **Partition (P1)** supports the **content extraction** (i.e., text segmentation and text segment classification) tasks and comprises 169 documents and gold standard annotations for page segments
* **Partition (P2)** contains 75 documents with a significantly richer set of annotations that consider content extraction, entities and slots. It supports benchmarking knowledge extraction tasks such as **entity recognition**, **entity classification**, **entity linking**,  and **slot filling** on top of the content extraction task.

Introducing paper: Slot Filling for Extracting Reskilling and Upskilling Options from the Web
CERBERUS DARPA Subterranean Challenge Datasets

Dataset link: https://github.com/leggedrobotics/cerberus_darpa_subt_datasets

Introducing paper: Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned
MSU HDR Video Reconstruction Benchmark

This is a dataset for a video inverse-tone-mapping task. The dataset contains various contents for the task of restoring HDR video: fireworks, flowers, football, night city, scenes with reflections. Videos have different brightness ranges and contain different types of lighting. The camera for shooting the dataset captures 14 stops of the dynamic range.
Multilingual Persuasion Detection

This dataset contains dialogue lines from the games Knights of the Old Republic 1 & 2 and Neverwinter Nights 1. Some of the dialogue lines are marked as persuasive (which is when the player character is attempting a Persuade skill check.) 

If you use this data, please cite:

Pöyhönen, T., Hämäläinen, M., Alnajjar, K. (2022) "Multilingual Persuasion Detection: Video Games as an Invaluable Data Source for NLP" DiGRA '22 - Proceedings of the 2022 DiGRA International Conference

Introducing paper: Multilingual Persuasion Detection: Video Games as an Invaluable Data Source for NLP