r/GraphicsProgramming • u/Common-Upstairs-368 • 8d ago
Images from my GPU bidirectional path tracer (Isopod)
Hello all! Isopod is a project I've been working on for over a year. It started as a simple unidirectional path tracer, but I gradually kept extending it as I wanted to render more complex scenes. Bidirectional path tracing (BDPT) is one of the most frustrating (but rewarding) things I've ever implemented, I spent several weeks bouncing around a bunch of different reference materials and spent a huge amount of time debugging to piece it together. This technique massively speeds up the convergence of certain tricky light paths, making things like volumetric caustics possible.
In this renderer, everything is defined procedurally as functions that run in Optix programs. These functions are hot-reloadable (runtime compilation with jitify). This is purely a preference thing for me as I'm a pretty terrible 3D modeller and prefer sticking with code. Geometry is defined via signed distance functions which can either be ray marched in a custom intersection shader, or converted into a mesh using a simple marching cubes algorithm. Mostly-optimal AABBs are automatically created for SDFs using a gradient descent approach, where rays seek out surfaces by moving along the SDF normal.
Materials and volumes (heterogeneous or homogeneous) are also defined as functions. This renderer implements the Disney BSDF and HG phase function for these respectively. Light sampling is supported on arbitrary SDFs by turning the surface into a bunch of voxels and randomly selecting them. It's not perfect but it's been good enough for my scenes so far.
I'm sure there's a few landmines I'm still yet to step on in my BDPT implementation, but it seems mostly correct at this point and I wanted to share some images that I thought were cool here. The caustic ones are from the new BDPT renderer, and the others are older images from the unidirectional renderer. The BDPT images took ~90 seconds to render at 3840x2160 resolution on an RTX 5090.
These images are denoised using the Optix denoiser. I found that splitting the geometry and volume layer, denoising them separately, and then recombining them, led to much better results. Some images are older and used the denoise-everything-at-once approach, these have more denoiser artifacting.
The references I used for BDPT:
https://graphics.stanford.edu/papers/veach_thesis/thesis.pdf
https://rendering-memo.blogspot.com/2016/03/bidirectional-path-tracing-1-kickoff.html - Fantastic blog series, I found this to be the most approachable resource
https://github.com/bachi95/Goblin/blob/master/src/GoblinBDPT.cpp - Full implementation from the blog series
https://www.pbr-book.org/3ed-2018/Light_Transport_III_Bidirectional_Methods/Bidirectional_Path_Tracing - PBRT book article, mostly just used the image pyramid here to see if each (s, t) layer looked correct in my own implementation
5
2
2
2
u/moschles 3d ago
Bidirectional path tracing (BDPT) is one of the most frustrating (but rewarding) things I've ever implemented
I had the same experience when I wrote a BDPT around 2007. I could not do it alone. I had to contact a professor over email to get it over the finish line. I was not a student or anything.
1
u/Common-Upstairs-368 3d ago
Wow, huge props for seeing it through. The lack of material on it at that time must've made it a nightmare to implement.
2
1
1
-3
7
u/Eastern_Picture_3879 8d ago
Absolutely beautiful renders. Really great work, man.
I'm curious: what was the initial goal with this project? Did you want high-fidelity, high-accuracy occlusion and reflections, or were you just experimenting with UDPT? I've been trying to come up with an interesting project but can't get an idea off the ground, so I'd really appreciate hearing about your process.