Omkar2118/datasets huggingface dataset:
VIST-E
Full name: VIST-Ending

VIST-E consists of 49,913 training samples, 4,963 validation samples and 5,030 test samples, which is modified from VIST dataset. As every sample in VIST contains a story of five sentences, each sample in VIST-E contains the story ending, the ending-related image and the first four sentences in the story as the story context. Additionally, each sentence is trimmed down to a maximum of 40 words.

Introducing paper: IgSEG: Image-guided Story Ending Generation
LSMDC-E
Full name: LSMDC-Ending

LSMDC-E contains 20,151 training samples, 1,477 validation samples and 2,005 test samples, which is modified from LSMDC 2021. We take the first four sentences in every five-sentence story as the story context and the last sentence as the story ending. As every sentence relates to a movie frame set in LSMDC, we take the last frame set as the ending-related image set for IgSEG.

Introducing paper: MMT: Image-guided Story Ending Generation with Multimodal Memory Transformer
BUP20
Full name: Sweet Pepper 2020 University of Bonn

Video sequences from a glasshouse environment in Campus Kleinaltendorf(CKA), University of Bonn, captured by [PATHoBot](https://ieeexplore.ieee.org/document/9562047), a glasshouse monitoring robot. 

- 10 Video sequences, 120s long.
- 2 cultivar Mavera (yellow) and All- rounder (red).
- RGB-D images (Intel RealSense D435i cameras).
- Robot odometry and IMU.
- High quality sparese instance segmentation labels.

Introducing paper: PATHoBot: A Robot for Glasshouse Crop Phenotyping and Intervention