Given a short query with keyphrases about a research idea in 2009 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: I want to train a model for depth estimation from images.

Keyphrases: depth estimation images

Dataset description:
ITOP: The ITOP dataset consists of 40K training and 10K testing depth images for each of the front-view and top-view tracks. This dataset contains depth images with 20 actors who perform 15 sequences each and is recorded by two Asus Xtion Pro cameras.
DIODE: Diode Dense Indoor/Outdoor DEpth (DIODE) is the first standard dataset for monocular depth estimation comprising diverse indoor and outdoor scenes acquired with the same hardware setup. The training set consists of 8574 indoor and 16884 outdoor samples from 20 scans each.
Middlebury: The Middlebury Stereo dataset consists of high-resolution stereo sequences with complex geometry and pixel-accurate ground-truth disparity data. The ground-truth disparities are acquired using a novel technique that employs structured lighting and does not require the calibration of the light projectors.
KITTI-Depth: The KITTI-Depth dataset includes depth maps from projected LiDAR point clouds that were matched against the depth estimation from the stereo cameras. The depth images are highly sparse with only 5% of the pixels available and the rest is missing.

Options:- A: ITOP  B: DIODE  C: Middlebury  D: KITTI-Depth
Middlebury