I’ve been going through the CVPR 2024 papers and noticed that several focus on diffusion models, particularly in relation to Point Clouds. As someone who is quite new to this concept, I’m looking for a good starting point to better understand diffusion models and their application to Point Clouds.
Can anyone recommend resources, tutorials, or foundational papers that would help me get up to speed with this topic? I’m hoping to save time and energy by starting with the most relevant and useful material.
To get started with diffusion models and their application to Point Clouds, you might begin with “Denoising Diffusion Probabilistic Models” by Ho et al. (2020) for a fundamental understanding of diffusion models. For a review of various diffusion models and their uses, check out “Diffusion Models: A Comprehensive Review” by Yang Song and Stefano Ermon. To focus specifically on Point Clouds, “Point Cloud Generation with Conditional Diffusion Models” by Zhengqi Li et al. (2023) and “Learning to Generate Point Clouds with Diffusion Models” by Xie et al. (2024) offer detailed insights. Additionally, tutorials like “A Beginner’s Guide to Diffusion Models” on Towards Data Science and relevant YouTube lectures can provide a more accessible introduction to these concepts.
If you’re new to diffusion models in point clouds, start by learning about point clouds and diffusion models. Read key papers on the topic, explore their use in point clouds, try practical examples, and join relevant communities for guidance. This will help you understand and work with these models effectively.
Start with Fooocus, the most popular SD tool for beginners, and then explore its advanced features. To learn more about specific aspects, use Google, Reddit, or YouTube. Then, move on to A1111, SDNext, Forge, and ComyfUI.
