Summary of Screenwriter: Automatic Screenplay Generation and Movie Summarisation, by Louis Mahon et al.
ScreenWriter: Automatic Screenplay Generation and Movie Summarisation
by Louis Mahon, Mirella Lapata
First submitted to arxiv on: 17 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computer Vision and Pattern Recognition (cs.CV); Multimedia (cs.MM)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes automatic screenplay generation from video content, which can be used for summarization. The task is challenging due to the need to identify character intentions and long-range temporal dependencies. Existing methods rely on textual screenplays as input, limiting their applicability. The proposed method, ScreenWriter, operates only on video and produces output that includes dialogue, speaker names, scene breaks, and visual descriptions. It uses a novel algorithm for scene segmentation based on visual vectors and a novel method for determining character names from a database of actor faces. The automatic screenplays can be used to generate plot synopses with a hierarchical summarization method based on scene breaks. The quality of the final summaries is tested on the MovieSum dataset, which is augmented with videos, showing that they are superior to comparison models that assume access to goldstandard screenplays. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about creating automatic movie summaries from video content. This can be helpful for people who want to remember key plot points or get an overview of a movie without watching the whole thing. The task is difficult because it requires understanding what characters are trying to do and how events will unfold over time. Most current methods rely on having a script, which limits their usefulness. The new method only uses the video and produces a summary that includes dialogue, character names, scene breaks, and descriptions of what’s happening visually. This can be used to create a shorter summary of the movie’s plot. The quality of these summaries is tested against other methods that assume they have access to a perfect script. |
Keywords
» Artificial intelligence » Summarization
