Given a short query with keyphrases about a research idea in 2017 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 learn a model that takes two vehicle images and their spatio-temporal information as

Keyphrases: vehicle re-identification video

Dataset description:
ConvAI2: The ConvAI2 NeurIPS competition aimed at finding approaches to creating high-quality dialogue agents capable of meaningful open domain conversation. The ConvAI2 dataset for training models is based on the PERSONA-CHAT dataset.
Composable activities dataset: The Composable activities dataset consists of 693 videos that contain activities in 16 classes performed by 14 actors. Each activity is composed of 3 to 11 atomic actions.
VeRi-776: VeRi-776 is a vehicle re-identification dataset which contains 49,357 images of 776 vehicles from 20 cameras. The dataset is collected in the real traffic scenario, which is close to the setting of CityFlow.
ActivityNet-QA: The ActivityNet-QA dataset contains 58,000 human-annotated QA pairs on 5,800 videos derived from the popular ActivityNet dataset. The dataset provides a benchmark for testing the performance of VideoQA models on long-term spatio-temporal reasoning.

Options:- A: ConvAI2  B: Composable activities dataset  C: VeRi-776  D: ActivityNet-QA
VeRi-776