Given a short query with keyphrases about a research idea in 2020 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: D3VO -- A new deep framework for direct visual odometry.

Keyphrases: monocular visual odometry image sequences

Dataset description:
TUM Visual-Inertial Dataset: A novel dataset with a diverse set of sequences in different scenes for evaluating VI odometry. It provides camera images with 1024x1024 resolution at 20 Hz, high dynamic range and photometric calibration.
AMASS: AMASS is a large database of human motion unifying different optical marker-based motion capture datasets by representing them within a common framework and parameterization. AMASS is readily useful for animation, visualization, and generating training data for deep learning.
ADVIO: Provides a wide range of raw sensor data that is accessible on almost any modern-day smartphone together with a high-quality ground-truth track.
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.

Options:- A: TUM Visual-Inertial Dataset  B: AMASS  C: ADVIO  D: KITTI
KITTI