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⚡️ Introducing Bolt3D ⚡️ Bolt3D generates interactive 3D scenes in less than 7 seconds on a single GPU from one or more images. It features a latent diffusion model that directly generates 3D Gaussians of seen and unseen regions, without any test time optimization. 🧵👇 (1/9)

Stan Szymanowicz

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126,142 görüntüleme • 1 yıl önce •via X (Twitter)

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Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Project page: Arxiv: A huge shout out to my absolutely incredible co-authors @jasonyzhang2 @_pratul_ @RuiqiGao @ArthurBrussee @holynski_ @rmbrualla @jon_barron @philipphenzler (2/9)

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Generating 3D content is challenging because (1) It is unclear how to represent and structure (possibly unbounded) 3D scene data for diffusion models. (2) 3D data is much more limited than 2D image and video data. (3/9)

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Bolt3D puts 3D data in 2D grids (remember Splatter Images?). First, we sample multi-view images and pointmaps with a latent diffusion model. Then, the properties of 3D Gaussians are estimated with a Gaussian head. We reconstruct a large dataset of 3D scenes for training. (4/9)

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

The key to generating high-quality geometry with a latent diffusion is to train a VAE for geometry data (pointmaps). We found that, for geometry data, our transformer decoder is more appropriate than a convolutional decoder, and that RGB image VAEs fail catastrophically. (5/9)

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Bolt3D can accept variable number of input images. Our model adheres to conditioning when it is available and generates unobserved scene regions without any re-projection or in-painting mechanisms. (6/9)

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Bolt3D enables generative capabilities in feed-forward 3D reconstructors. Compared to SOTA optimization-based pipelines (first generate Novel Views, then distill 3D), Bolt3D reduces inference cost by 64-300x. (7/9)

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Check out the generated 3D scenes in our interactive viewer, powered by Brush, as well as more video results on the project website! (8/9)

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Finally, a special thank you to @poolio for his helpful suggestions, guidance and contributions! (9/9)

clem 🤗 profil fotoğrafı

clem 🤗1 yıl önce

would be so cool to have a to try!

Matthias Niessner profil fotoğrafı

Matthias Niessner1 yıl önce

Great work!

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Thank you!

Hang Gao profil fotoğrafı

Hang Gao1 yıl önce

Nice work!

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Thank you!

Jensen Zhou profil fotoğrafı

Jensen Zhou1 yıl önce

@hangg70 Hi y'all, let me introduce you two.

Hang Gao profil fotoğrafı

Hang Gao1 yıl önce

@StanSzymanowicz Amesome!

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

@jensenzhoujh The two camera-conditioned-NVS experts!

Qianyi Wu profil fotoğrafı

Qianyi Wu1 yıl önce

Impressive results!

Abdullah Hamdi profil fotoğrafı

Abdullah Hamdi1 yıl önce

Amazing !

Samarth Sinha profil fotoğrafı

Samarth Sinha1 yıl önce

Congrats Stan!!

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Thanks Sam!

Arjun Karpur profil fotoğrafı

Arjun Karpur1 yıl önce

Congrats on the release, Stan!

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Thanks Arjun!

Markus Malmros profil fotoğrafı

Markus Malmros1 yıl önce

Wow, looks really cool!

tipatat profil fotoğrafı

tipatat1 yıl önce

Really impressive work! Would it be possible to improve the quality with a large data set of high quality 3DGS made of real world capture?

Nataniel Ruiz profil fotoğrafı

Nataniel Ruiz1 yıl önce

amazing

Hirokatsu Kataoka | 片岡裕雄 profil fotoğrafı

Hirokatsu Kataoka | 片岡裕雄1 yıl önce

Amazing tech, congratulations Stan! 🎉

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Thanks Hirokatsu!

Bilawal Sidhu profil fotoğrafı

Bilawal Sidhu1 yıl önce

Very cool results, congrats!

Haofei Xu profil fotoğrafı

Haofei Xu1 yıl önce

Fantastic results! Congrats!

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Thanks Haofei!

Rundi Wu profil fotoğrafı

Rundi Wu1 yıl önce

Great work and awesome results! Congrats Stan!

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Thanks Rundi!

Nikita Karaev profil fotoğrafı

Nikita Karaev1 yıl önce

Super cool! Congrats Stan!

Stan Szymanowicz profil fotoğrafı

Stan Szymanowicz1 yıl önce

Thank you Nikita!

BLd profil fotoğrafı

BLd1 yıl önce

Congrats, results are outstanding!

:3 profil fotoğrafı

:31 yıl önce

In 2020 I made a framework that can generate cities at ~10 million vertices in 16.667ms, meaning that you can generate a whole game map 60 times per second while playing the game, and everything is fully interactive and hierarchically laid out:

Kosta Derpanis at #ECCV2026 🇸🇪 profil fotoğrafı

Kosta Derpanis at #ECCV2026 🇸🇪1 yıl önce

💪

TOTORITO profil fotoğrafı

TOTORITO1 yıl önce

Waaawwww !!!

The Qubits Guy profil fotoğrafı

The Qubits Guy1 yıl önce

When will @Apple license your tech for my next iPhone?

MOTA profil fotoğrafı

MOTA1 yıl önce

release the kraken

MangoMagic™️ profil fotoğrafı

MangoMagic™️1 yıl önce

Fascinating tech or just a new way to procrastinate? #3DJustGotReal #WhereIsMyGPU #ProcrastinationStation

iKrasinski profil fotoğrafı

iKrasinski1 yıl önce

Amazing. Waiting for the HF space to feel with my hands.

Simsalabim profil fotoğrafı

Simsalabim1 yıl önce

Congrats, looks great! Any Plans on releasing the code? Would love to try it out!

Diego Bonati profil fotoğrafı

Diego Bonati1 yıl önce

looks very interesting, I would like to generate stereoscopic images with this and also VR equirectangular format.

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