You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: Human is capable of one-shot learning [22, 23, 42]. For instance, given a video paired with a textual description of “a man is skiing on snow” as a hint, we might hallucinate how a panda skis on snow if we could picture what a panda looks like.Since T2I models pre-trained with large-scale image-text data already capture the knowledge of open-domain concepts,an intuitive question arises:can it infer other novel videos from a single video example like human beings?A new T2V generation problem is therefore introduced, namely, One-Shot Video Generation, where only a single text-video pair is presented for training an open-domain T2V generator.The generator is expected to capture necessary motion knowledge from the input video and synthesize novel videos guided by edited prompts.

Question: Is there any limitation of this technique?
Training with opendomain data, it is hard to capture necessary motion knowledge from the input video and synthesize novel videos guided by edited prompts