Live Video Comment Generation Based on Surrounding Frames and Live Comments
This addresses the need for interactive and relevant comment generation in live video platforms, but it is incremental as it builds on existing comment generation tasks.
The paper tackles the problem of generating live comments for videos by creating a new dataset and proposing an end-to-end model that uses video frames and other users' comments. Experimental results show the method significantly outperforms baselines.
In this paper, we propose the task of live comment generation. Live comments are a new form of comments on videos, which can be regarded as a mixture of comments and chats. A high-quality live comment should be not only relevant to the video, but also interactive with other users. In this work, we first construct a new dataset for live comment generation. Then, we propose a novel end-to-end model to generate the human-like live comments by referring to the video and the other users' comments. Finally, we evaluate our model on the constructed dataset. Experimental results show that our method can significantly outperform the baselines.