DNerf-Pytorch

Implementation of paper D-Nerf: Neural Randiance Fields for Dynamic Scenes

Nerf (v18)	T-Nerf (v2)

Novel Views

Camera	Time	Camera + Time

Hyperparameters:

Parameters	Values
Iteration	200K
Scheduler	Exponential Decay
Scheduler Step	160K approx.
Rays Sample	1024
Crop	0.5
Pre Crop Iter	50
Factor	2
Near Plane	2.0
Far Plane	6.0
Height	800 / factor
Width	800 / factor
Downscale	2
lr	5e-4
lrsch_gamma	0.1
Pos Enc Dim	10
Dir Enc Dim	4
Num Samples	64
Num Samples Fine	128
Net Dim	256
Net Depth	8
Inp Feat	2*(num_channels*pos_enc_dim) + num_channels
Dir Feat	2*(num_channels*dir_enc_dim) + num_channels
Time Feat	2*(1*dir_enc_dim) + 1

References:

[1] Computer Graphics and Deep Learning with NeRF using TensorFlow and Keras []

[2] 3D volumetric rendering with NeRF []

[3] Nerf Official Colab Notebook []

[4] NeRF PyTorch [] ( Special Thanks :) )

[5] PyTorch Image Quality (PIQ) []