Unable to reproduce results on Realistic Synthetic 360 scenes

[NagabhushanSN95]

Hi,

I am trying to reproduce the results on Realistic Synthetic 360 - lego scene. I tried the configs released in this GitHub repo as well as the configs mentioned in issue-2. But I was not able to get anywhere close to the reported performance with either of the configs. Any suggestions on how to figure out what is happening? I've attached both the configs below for reference. Kindly let me know if you need any other information.

Configs from this GitHub repo:

datadir = ../Data/Databases/NeRF_Synthetic/Data1/lego
expname = lego
basedir = ../Runs/Training/Train0034
dataset_type = blender
train_scene = [26, 86, 2, 55]
factor = 1

N_rand = 1024
N_samples = 64
N_importance = 128
use_viewdirs = True
no_batching = True
lrate_decay = 500
white_bkgd = True

precrop_iters = 500
precrop_frac = 0.5

entropy = True
N_entropy = 1024
entropy_ray_zvals_lambda = 0.001
fewshot = 4

wandb = False
i_wandb = 10

N_iters = 50000
i_weights = 25000

Configs from issue-2:

datadir = ../Data/Databases/NeRF_Synthetic/Data1/lego
expname = lego
basedir = ../Runs/Training/Train0034
dataset_type = blender
train_scene = [26, 86, 2, 55]
factor = 1

N_rand = 1024
N_samples = 64
N_importance = 128
use_viewdirs = True
no_batching = True
lrate_decay = 500
white_bkgd = True

precrop_iters = 500
precrop_frac = 0.5

entropy = True
N_entropy = 1024
entropy_ray_zvals_lambda = 0.001
fewshot = 4

smooth_sampling_method = near_pixel
smooth_pixel_range = 1
smoothing_activation = softmax
smoothing_lambda = 0.00001
smoothing_step = 2500

wandb = False
i_wandb = 10

N_iters = 50000
i_weights = 25000