Omkar2118/datasets huggingface dataset:
OIVIO
Full name: A Benchmark for Visual-Inertial Odometry Systems Employing Onboard Illumination

It consists of 36 sequences, recorded in mines, tunnels, and other dark environments, totaling more than 145 minutes of stereo camera video and IMU data. In each sequence, the scene is illuminated by an onboard light of approximately 1350, 4500, or 9000 lumens. We accommodate both direct and indirect VIO methods by providing the geometric and photometric camera calibrations. The full dataset, including sensor data, calibration sequences, and evaluation scripts can be downloaded here.
UMA-VI Dataset
Full name: The UMA-VI dataset: Visual--inertial odometry in low-textured and dynamic illumination environments

The dataset contains 32 sequences for the evaluation of VI motion estimation methods, totalling ∼80 min of data. The dataset covers challenging conditions (mainly illumination changes and low textured environments) in different degrees and a wide rage of scenarios (including corridors, parking, classrooms, halls, etc.) from two different buildings at the University of Malaga. In general, we provide at least two different sequences within the same scenario, with different illumination conditions or following different trajectories. All sequences were recorded with our VI sensor handheld, except a few that were recorded while mounted in a car.
AIROGS
Full name: Rotterdam EyePACS AIROGS

The Rotterdam EyePACS AIROGS dataset (in full, so including train and test) contains 113,893 color fundus images from 60,357 subjects and approximately 500 different sites with a heterogeneous ethnicity.
CRCDX
Full name: TCGA-CRC-DX

Histological images of colorectal cancer, derived from the TCGA database
Objaverse

**Objaverse** is a large dataset of objects with 800K+ (and growing) 3D models with descriptive captions, tags, and animations. Objaverse improves upon present day 3D repositories in terms of scale, number of categories, and in the visual diversity of instances within a category.

Source: [Objaverse: A Universe of Annotated 3D Objects](https://arxiv.org/pdf/2212.08051v1.pdf)

Image Source: [https://objaverse.allenai.org/](https://objaverse.allenai.org/)

Introducing paper: Objaverse: A Universe of Annotated 3D Objects
multiRAW

To encourage reproducible research, a labeled MultiRAW dataset containing>7k RAW images acquired using multiple camera sensors is made publicly accessible for RAW-domain processing.

Provide:
* four cameras RAW images
* corresponding RGB images
* detection labels
* segmentation labels

Introducing paper: Efficient Visual Computing with Camera RAW Snapshots
ROSCOE

**ROSCOE** is a suite of interpretable, unsupervised automatic scores that improve and extend previous text generation evaluation metrics.

Source: [ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning](https://arxiv.org/pdf/2212.07919v1.pdf)

Image Source: [https://arxiv.org/pdf/2212.07919v1.pdf](https://arxiv.org/pdf/2212.07919v1.pdf)

Introducing paper: ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning
Robust Summarization Evaluation Benchmark

**Robust Summarization Evaluation Benchmark** is a large human evaluation dataset consisting of over 22k summary-level annotations over state-of-the-art systems on three datasets.

Source: [Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation](https://arxiv.org/pdf/2212.07981v1.pdf)

Introducing paper: Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation