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💥 Think more real data is needed for scene reconstruction? Think again! Meet MegaSynth: scaling up feed-forward 3D scene reconstruction with synthesized scenes. In 3 days, it generates 700K scenes for training—70x larger than real data! ✨ The secret? Reconstruction is mostly non-semantic! No need to rely heavily on... show more
26,832 görüntüleme • 1 yıl önce •via X (Twitter)
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🔍 How does MegaSynth work? MegaSynth focuses on basic geometric structures, using augmented non-semantic shape primitives combined with randomized lighting and materials. It enhances data scalability, control, diversity, and provides accurate metadata for training models. (2/4)

📈 MegaSynth delivers results! Training with MegaSynth consistently improves performance across models, testing scenarios, and training settings. It enhances handling of complex lighting, materials, thin structures, and cluttered scenes—highlighting the power of synthesized data! (3/4)

🤯 Surprising insight. Training with zero real data performs comparably, confirming that multi-view reconstruction is largely non-semantic and low-level—aligning with observations from optimization-based methods like NeRF and COLMAP. (4/4)

Joint work with @zexiangxu , @DesaiXie , @chenziwee , @Haian_Jin , @fujun_luan , Zhixin Shu, @KaiZhang9546 , @Sai__Bi , Xin Sun, Jiuxiang Gu, @qixing_huang , @geopavlakos and @HaoTan5

Awesome! Do you happen to have an estimated timeline for the release of the data?

Thanks for your interest. It should be very quick, probably in January

What license are you using for datasets ?

Looks really interesting! Would it be able to handle object centric reconstruction too?

Yes it works. Object-centric is easier 😁

How about real+synthetic combined ? Can it boost performance further ?
