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Check out our fun work on robust view synthesis! 🤩 Using a casual video as input, our method jointly 1⃣estimates accurate camera poses and 2⃣reconstructs multiple local radiance fields for a large scene. Project🕸️:
35,526 Aufrufe • vor 3 Jahren •via X (Twitter)
8 Kommentare

HOW-TO: Estimating accurate poses? 👉 Progressively optimize both radiance fields and poses. HOW-TO: Modeling large scenes? 👉 Dynamically allocate local radiance fields

How could we handle large scenes? 🤔 a) Normalized Device Coordinate (NDC): 👉 Only work for forward-facing scenes b) Space contraction: 👉 Work best for inward-facing scenes c) Generic scenes: 👉 Allocate multiple local radiance fields along the camera trajectory

This is @AndreasMeuleman's intern project with Meta last summer, in collaboration with many talented people: Yu-Lun Liu, @gaochen315, @_ChangilKim, Min H. Kim, @JPKopf We will release both the code and data soon! 😍 Stay tuned!

We will be presenting this paper at #CVPR2023! Looking forward to seeing you all there. Come chat with us for any questions!

Oh my, the results look amazing! 😍 But can video stabilization methods work just as well? 🤔 Unfortunately, *2D* video stabilization methods cannot handle these large viewpoint changes. Look how shaky the results (from Fusta are on these casual videos!

Also check out another excellent work (also at #CVPR2023) with a similar capability of handling free camera trajectories!

Looks really good and stable!! Congrats🎉

Results look great, congrats to the team! Will be excited to play around with the repo once released.
