Row 66268

Row ID: 66268 | Dataset Entry | Axioma AXP Content Repository

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I am doing my MSc and I've chosen to do a video generation project. I've read some papers on image and video synthesis:

* VQGAN * Stable Diffusion * Imagen

I also picked 3 video generation papers:

* Video-LDM * Stable Video Diffusion fine-tuned for Multi-View generation (SVD-MV) * Text2Video-Zero

I also read some survey papers, and those are the models I've chosen to talk about.

What i'm struggling with is to pick a logically ordered papers, so first I explain the 3 image generation papers, and the video generation papers should follow the same strategies mentioned in the image synthesis papers.

Can I ask you to suggest different set of papers to write about? I can still change all of the papers to something else.

Something that is mostly recent (2020-2024 is fine) and has some big impact. I know for example VQGAN is popular base model, the techniques and strategies used in the paper are still relevant today.

Imagen (by Google) however, is not open source, and I prefer papers with open source code. That's why I avoid OpenAI papers.

I also read that diffusion is chosen over GAN in video generation because it has better results, both in quality and training. However, diffusion is more computationally expensive.

Video-LDM for example is based on Stable Diffusion, so for me its good papers to talk about.

FieldValue
text I am doing my MSc and I've chosen to do a video generation project. I've read some papers on image and video synthesis: * VQGAN * Stable Diffusion * Imagen I also picked 3 video generation papers: * Video-LDM * Stable Video Diffusion fine-tuned for Multi-View generation (SVD-MV) * Text2Video-Zero I also read some survey papers, and those are the models I've chosen to talk about. What i'm struggling with is to pick a logically ordered papers, so first I explain the 3 image generation papers,…
label r/machinelearning
dataType post
communityName r/MachineLearning
datetime 2024-05-23
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url_encoded Z0FBQUFBQm5Lak9zWGpaMkNZWE0tZVFwVlBlRmthcXc4N2d6a3RPOHV3Zm1PMWF1Z29yMDlRc0lPczF2V2Rvb0VFVV8tYVo0RVJycnlqcXJMU2Y1VFFobExCRGJwYWR6ZTNINWtYZF8zaUdvRGxscHJQdDRjbkJtQnlNdTBBVWFOX2F3bDNURU9MMUhKeU9WTjBSUG5RNzRsU2NITHlYczQ5UnpBT2JLR1RCUENCSEJ0SE0ya1Z6TlV1eTl4ZFpZT1NhX0lObEg2c3NORmkzcllYRFZ2VUk5czlSM09hQmtEUT09

Raw Record

{
  "text": "I am doing my MSc and I've chosen to do a video generation project. I've read some papers on image and video synthesis:\n\n* VQGAN\n* Stable Diffusion\n* Imagen\n\nI also picked 3 video generation papers:\n\n* Video-LDM\n* Stable Video Diffusion fine-tuned for Multi-View generation (SVD-MV)\n* Text2Video-Zero\n\nI also read some survey papers, and those are the models I've chosen to talk about.\n\nWhat i'm struggling with is to pick a logically ordered papers, so first I explain the 3 image generation papers, and the video generation papers should follow the same strategies mentioned in the image synthesis papers.\n\nCan I ask you to suggest different set of papers to write about? I can still change all of the papers to something else.\n\nSomething that is mostly recent (2020-2024 is fine) and has some big impact. I know for example VQGAN is popular base model, the techniques and strategies used in the paper are still relevant today.\n\nImagen (by Google) however, is not open source, and I prefer papers with open source code. That's why I avoid OpenAI papers.\n\nI also read that diffusion is chosen over GAN in video generation because it has better results, both in quality and training. However, diffusion is more computationally expensive.\n\nVideo-LDM for example is based on Stable Diffusion, so for me its good papers to talk about.",
  "label": "r/machinelearning",
  "dataType": "post",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-23",
  "username_encoded": "Z0FBQUFBQm5Lak1jYkZNLVBKQXVnVjZIRGx3NkljTHhzOGdZLXotSGRoY3FRLUZ0czBoRDRuN2RVd3FpN1o0RGJhd3lKVGpaREVsZFZBZ0ZSTzlTQk02QWliak45M05DUVE9PQ==",
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}
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