Practical Product Path Guiding Using Linearly Transformed Cosines

Stavros Diolatzis¹, Adrien Grusson², Wenzel Jakob³, Derek Nowrouzezahrai², George Drettakis¹

¹ Université Côté d'Azur, Inria, ² McGill University, ³ EPFL

Comparison between Ours and [HEV*16]

We do not use Russian roulette and set the BSDF sampling probability to 0.25 for both techniques. The training time for the GMMs are shown below:

Scene	Training time
Necklace	59 sec
Glossy Kitchen	172 sec
Living room	143 sec
Attic	177 sec

Living room (5 min)

Glossy Kitchen (10 min)

Necklace (5 min)

Attic (10 min)

Comparison between Ours and [MGN17]

Living room (2 min)

Glossy Kitchen (5 min)

Necklace (3 min)

Pink Kitchen (3 min)

Attic (3 min)

Bathroom (3 min)

Comparison between BSDF sampling and LTC based BSDF sampling

We demonstrate same sample results of the two sampling methods. For the LTC based BSDF sampling we do the same hierarchical sampling scheme but ignoring the incoming radiance and ensuring we reach a certain depth.

Living room (150 spp)

Glossy Kitchen (150 spp)

Necklace (150 spp)

Pink Kitchen (150 spp)

Attic (150 spp)

Bathroom (150 spp)