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Inquiry Regarding Temporal Coherence in Extended Video Generation #4
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Thank you for your attention to our work.
Regarding your questions, I'll summarize them: How do we ensure the consistency between multiple video snippets generated by Vlogger when creating long videos?
Firstly, for a complete story, it should logically be coherent so that we have a reason to expect the generated video content to be consistent.
Then, for such a story, in the planning phase, we ask LLM to preserve the plot of the original story as much as possible, without changing the timeline and development path. This way, we approximately assume that the plot in the obtained script is coherent and acceptable.
Next is how to ensure that the vlog generated from the script is visually consistent. We use reference images to some extent to address this issue. If users can see the same or similar main characters or scenes, they often perceive it as a video shot for the same story. However, this method currently has limitations, as it may not consider very fine-grained consistency since reference images provide more of a global reference.
In fact, we initially considered using a transition model to generate transition videos between videos that should have coherence, such as SEINE. However, the results did not meet our expectations entirely, so we have not included this part in our open-source code for now. I believe this could be an interesting direction to explore further.
I'm glad someone has thought of this. I hope the information above is helpful to you.
Shaobin Zhuang
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发件人: "zhuangshaobin/Vlogger" ***@***.***>;
发送时间: 2024年1月22日(星期一) 下午2:51
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主题: [zhuangshaobin/Vlogger] Inquiry Regarding Temporal Coherence in Extended Video Generation (Issue #4)
Dear Vlogger Development Team,
I hope this message finds you well. I am reaching out to express my commendations on the remarkable strides you have made with the Vlogger system in generating minute-level video blogs. The innovative approach of integrating a Large Language Model as a director, alongside foundation models as vlog professionals, is truly impressive.
However, I have a query pertaining to the temporal coherence in the extended video generation process. As you are aware, maintaining continuity and a seamless narrative over longer durations can be quite challenging, especially when transitioning between diverse scenes in a vlog.
Could you kindly elaborate on the mechanisms that Vlogger employs to ensure temporal coherence and narrative consistency throughout the entirety of a minute-level vlog? Additionally, are there any specific strategies in place to handle potential discrepancies that might arise during scene transitions?
I am particularly interested in understanding how the system manages the storyline's continuity, considering the complexity of human-like planning and execution that is required for extended video content.
Thank you for your time and consideration. I eagerly await your response, as I believe it would greatly benefit the academic community and industry practitioners alike.
Best regards,
yihong1120
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Dear Vlogger Development Team,
I hope this message finds you well. I am reaching out to express my commendations on the remarkable strides you have made with the Vlogger system in generating minute-level video blogs. The innovative approach of integrating a Large Language Model as a director, alongside foundation models as vlog professionals, is truly impressive.
However, I have a query pertaining to the temporal coherence in the extended video generation process. As you are aware, maintaining continuity and a seamless narrative over longer durations can be quite challenging, especially when transitioning between diverse scenes in a vlog.
Could you kindly elaborate on the mechanisms that Vlogger employs to ensure temporal coherence and narrative consistency throughout the entirety of a minute-level vlog? Additionally, are there any specific strategies in place to handle potential discrepancies that might arise during scene transitions?
I am particularly interested in understanding how the system manages the storyline's continuity, considering the complexity of human-like planning and execution that is required for extended video content.
Thank you for your time and consideration. I eagerly await your response, as I believe it would greatly benefit the academic community and industry practitioners alike.
Best regards,
yihong1120
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