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OpenDAS
nerfacc
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6b8c91fd
"git@developer.sourcefind.cn:renzhc/diffusers_dcu.git" did not exist on "3d70777379eca6ea36527e978602f9adc40ae5fc"
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Commit
6b8c91fd
authored
Oct 09, 2022
by
Ruilong Li(李瑞龙)
Committed by
GitHub
Oct 09, 2022
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Update README.md
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README.md
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6b8c91fd
...
@@ -10,7 +10,7 @@ efficient volumetric rendering of radiance fields, which is universal and plug-a
...
@@ -10,7 +10,7 @@ efficient volumetric rendering of radiance fields, which is universal and plug-a
Using NerfAcc,
Using NerfAcc,
-
The
`vanilla NeRF`
model with 8-layer MLPs can be trained to
*better quality*
(+~0.5 PNSR)
-
The
`vanilla NeRF`
model with 8-layer MLPs can be trained to
*better quality*
(+~0.5 PNSR)
in
*1 hour*
rather than
*
1~2
days*
as in the paper.
in
*1 hour*
rather than
*days*
as in the paper.
-
The
`Instant-NGP NeRF`
model can be trained to
*better quality*
(+~0.7 PSNR) with
*9/10th*
of
-
The
`Instant-NGP NeRF`
model can be trained to
*better quality*
(+~0.7 PSNR) with
*9/10th*
of
the training time (4.5 minutes) comparing to the official pure-CUDA implementation.
the training time (4.5 minutes) comparing to the official pure-CUDA implementation.
-
The
`D-NeRF`
model for
*dynamic*
objects can also be trained in
*1 hour*
-
The
`D-NeRF`
model for
*dynamic*
objects can also be trained in
*1 hour*
...
...
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