One, in earlier works, the training samples were typically paired.

第一 在早期的作品中 训练样本通常是配对的。

After it has been exposed to enough training samples, it will be able to do this prediction by itself on unknown frames that it hasn't seen before.

学习过足够的训练样本后，它就能够在以前从没见过的视频帧上做预测。

However, a key difference here is that without such pairings, we don't need these labels, we can use significantly more training samples in our datasets which also helps the learning process.

然而 这里的一个重要区别是 没有这样的配对 我们不需要这些标签，我们可以在我们的数据集中使用更多的训练样本 这也有助于学习进程。