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𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗨𝗩𝗚𝗦 We introduce 𝗨𝗩𝗚𝗦, a new 2D representation of 3D Gaussian Splatting (3DGS) that leverages spherical mapping. Website: Paper:

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Nikolaos Sarafianos

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10,752 просмотров • 1 год назад •via X (Twitter)

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Фото профиля Nikolaos Sarafianos
Nikolaos Sarafianos1 год назад

- UVGS enables the application of image-based models for 3DGS feature extraction by representing it as multi-channel images. - We demonstrate effective compression of heterogeneous UVGS features and successful generalization of pre-trained 2D VAEs to this new representation.

Фото профиля Nikolaos Sarafianos
Nikolaos Sarafianos1 год назад

- Our new UVGS representation makes it effortless to leverage foundational 2D models, such as diffusion models, to directly generate 3DGS. Work with colleagues at Brown and Meta Reality Labs

Фото профиля David
David1 год назад

really cool!

Фото профиля Ziyu Wan
Ziyu Wan1 год назад

Impressive work!!! 🚀 Would love to see how this approach connects with our prior work 'Omage' ( - particularly regarding patch-structured UV mapping!

Фото профиля Nikolaos Sarafianos
Nikolaos Sarafianos1 год назад

I actually presented Omages (along with Geometry Image Diffusion from @DoctorDukeGonzo ) this week at a reading group; I really like this line of work. We'll be updating the arxiv in the next few days so we'll include a discussion related to Omages. See you in Singapore :)

Фото профиля Spenser Dickerson
Spenser Dickerson1 год назад

Very interesting!

Фото профиля Heshim🔥📛
Heshim🔥📛1 год назад

Can you train a generative AI on these 2d representations? Just to generate a family of odd 3d shapes and see what happens? For example, gather many 2d representations of cars… train an image model to generate these 2d multi channel images… then see what they look like in 3d?

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