Given a short query with keyphrases about a research idea in 2016 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: We introduce a new optical flow data cost by learning a density model for patches of flow error. This data

Keyphrases: optical flow estimation images autonomous driving

Dataset description:
CrowdFlow: The TUB CrowdFlow is a synthetic dataset that contains 10 sequences showing 5 scenes. Each scene is rendered twice: with a static point of view and a dynamic camera to simulate drone/UAV based surveillance.
Creative Flow+ Dataset: Includes 3000 animated sequences rendered using styles randomly selected from 40 textured line styles and 38 shading styles, spanning the range between flat cartoon fill and wildly sketchy shading. The dataset includes 124K+ train set frames and 10K test set frames rendered at 1500x1500 resolution, far surpassing the largest available optical flow datasets in size.
KITTI: KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) is one of the most popular datasets for use in mobile robotics and autonomous driving. It consists of hours of traffic scenarios recorded with a variety of sensor modalities, including high-resolution RGB, grayscale stereo cameras, and a 3D laser scanner.
SlowFlow: SlowFlow is an optical flow dataset collected by applying Slow Flow technique on data from a high-speed camera and analyzing the performance of the state-of-the-art in optical flow under various levels of motion blur.

Options:- A: CrowdFlow  B: Creative Flow+ Dataset  C: KITTI  D: SlowFlow
KITTI