Given a short query with keyphrases about a research idea in 2007 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 study unsupervised methods for stereo correspondence.

Keyphrases: dense stereo correspondence

Dataset description:
DIML/CVl RGB-D Dataset: This dataset contains synchronized RGB-D frames from both Kinect v2 and Zed stereo camera. For the outdoor scene, the authors first generate disparity maps using an accurate stereo matching method and convert them using calibration parameters.
DAVANet: A large-scale multi-scene dataset for stereo deblurring, containing 20,637 blurry-sharp stereo image pairs from 135 diverse sequences and their corresponding bidirectional disparities.
I-HAZE: The I-Haze dataset contains 25 indoor hazy images (size 2833×4657 pixels) training. It has 5 hazy images for validation along with their corresponding ground truth images.
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.

Options:- A: DIML/CVl RGB-D Dataset  B: DAVANet  C: I-HAZE  D: Middlebury
Middlebury