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Working on sparse volumetric light maps for WebGPU. Got generation part sorted. The resolution is adaptive, refining near geometry and skipping through most of the empty space. The video is question uses a map that's only 10MB in size, including everything. That's less the amount of GPU memory that... show more

Alex Goldring

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18,651 просмотров • 4 месяцев назад •via X (Twitter)

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Working on Sparse Volumetric Light-maps. Thanks to CynicatPro🎃 for pointing me at Unreal's version. In a nutshell it's just another sparse voxel data structure. My implementation is, no doubt, different from Epic Games Store's own. I'm using 4x4x4 probe grid with intermediate nodes having very wide branching factor of 64 as well (4x4x4). I liked the parameters that Unreal is using, of limiting both total memory as well as the lowest level of detail, which is common in sparse grid implementations. Here's Bistro scene with just 1Mb limit. This is roughly equivalent to a 512x512 lightmap texture in 2d, except surface light maps require unique UVs and you typically get very little detail out of 512 resolution texture with a lot of light leaking. There is also no directional response. My implementation encodes second-order spherical harmonics for each probe (9 coefficients), encoding RGB channels as RGBE9995 (4 bytes). So far only worked on the structure, actual bake is yet to come. I've been eyeing sparse voxel structures for a while now, and have been studying them roughly since the GigaVoxel paper by Cyril Crassin but never really implemented anything for the GPU before. I was always the BVH-kind of guy. It's a fascinating topic. --- Stats for the scene: --- Total memory usage: 1.000 MB Node count: 609 Unique probe count: 24,025 Probe reuse: 38.36 % Unexpanded nodes: 15,714 --- Again, note that there is no GI going on here, only the structure of the probe tree and the algorithm for building it from a given scene.

Working on Sparse Volumetric Light-maps. Thanks to CynicatPro🎃 for pointing me at Unreal's version. In a nutshell it's just another sparse voxel data structure. My implementation is, no doubt, different from Epic Games Store's own. I'm using 4x4x4 probe grid with intermediate nodes having very wide branching factor of 64 as well (4x4x4). I liked the parameters that Unreal is using, of limiting both total memory as well as the lowest level of detail, which is common in sparse grid implementations. Here's Bistro scene with just 1Mb limit. This is roughly equivalent to a 512x512 lightmap texture in 2d, except surface light maps require unique UVs and you typically get very little detail out of 512 resolution texture with a lot of light leaking. There is also no directional response. My implementation encodes second-order spherical harmonics for each probe (9 coefficients), encoding RGB channels as RGBE9995 (4 bytes). So far only worked on the structure, actual bake is yet to come. I've been eyeing sparse voxel structures for a while now, and have been studying them roughly since the GigaVoxel paper by Cyril Crassin but never really implemented anything for the GPU before. I was always the BVH-kind of guy. It's a fascinating topic. --- Stats for the scene: --- Total memory usage: 1.000 MB Node count: 609 Unique probe count: 24,025 Probe reuse: 38.36 % Unexpanded nodes: 15,714 --- Again, note that there is no GI going on here, only the structure of the probe tree and the algorithm for building it from a given scene.

Alex Goldring

11,487 просмотров • 4 месяцев назад

1 million unique objects in WebGPU. It appears to be the fashion to show off limits of one's engine. So here's "Shade" - my WebGPU engine running in the browser, rendering 1,000,000 unique meshes. That is - no instancing, and every mesh has a unique material, geometry and transform. We have full cascaded shadows here in the mix and post-processing stack. "Surely you can't have 1M instances, there's a trick, right?" - Nope. No tricks, just the state-of-the art Vizibility Buffer-based GPU-resident renderer. That is - on the CPU side we submit a fixed number of draw calls regardless of how many instances we have.

1 million unique objects in WebGPU. It appears to be the fashion to show off limits of one's engine. So here's "Shade" - my WebGPU engine running in the browser, rendering 1,000,000 unique meshes. That is - no instancing, and every mesh has a unique material, geometry and transform. We have full cascaded shadows here in the mix and post-processing stack. "Surely you can't have 1M instances, there's a trick, right?" - Nope. No tricks, just the state-of-the art Vizibility Buffer-based GPU-resident renderer. That is - on the CPU side we submit a fixed number of draw calls regardless of how many instances we have.

Alex Goldring

86,497 просмотров • 5 месяцев назад

Chaos and the double pendulum: the configuration space of the double pendulum is a torus (a circle for each angle coordinate) so we can plot the evolution of such a pendulum in two ways: either as a "real pendulum" in physical space, or as a point in configuration space :)

Chaos and the double pendulum: the configuration space of the double pendulum is a torus (a circle for each angle coordinate) so we can plot the evolution of such a pendulum in two ways: either as a "real pendulum" in physical space, or as a point in configuration space :)

Steve Trettel

149,856 просмотров • 2 лет назад

Sparse Volumetric Light maps (WebGPU). Worked on ensuring C0 continuity across the entire map. For now this is achieved by purging incomplete node levels, works well enough even if it's a bit of a blunt tool. Actual locations for probes during the bake are now going through an optimization phase, which allows me to push probes behind surfaces out into the open resulting in much fewer light leakage artifacts. This video here has only 28,376 probes in the map, and takes 1.8Mb of VRAM

Sparse Volumetric Light maps (WebGPU). Worked on ensuring C0 continuity across the entire map. For now this is achieved by purging incomplete node levels, works well enough even if it's a bit of a blunt tool. Actual locations for probes during the bake are now going through an optimization phase, which allows me to push probes behind surfaces out into the open resulting in much fewer light leakage artifacts. This video here has only 28,376 probes in the map, and takes 1.8Mb of VRAM

Alex Goldring

15,814 просмотров • 4 месяцев назад

[NeurIPS '24] DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation Abstract (excerpt) We introduce DreamMesh4D, a novel framework that combines mesh representation with sparse-controlled deformation technique to generate high-quality 4D object from a monocular video. To overcome the limitation of classical texture representation, we bind Gaussian splats to the surface of the triangular mesh for differentiable optimization of both the texture and mesh vertices. In particular, DreamMesh4D begins with a coarse mesh provided by a single image based 3D generation method. Sparse points are then uniformly sampled across the surface of the mesh, and are used to build a deformation graph to drive the motion of the 3D object for the sake of computational efficiency and providing additional constraint. For each step, transformations of sparse control points are predicted using a deformation network, and the mesh vertices as well as the bound surface Gaussians are deformed via a geometric skinning algorithm. The skinning algorithm is a hybrid approach combining LBS (linear blending skinning) and DQS (dual-quaternion skinning), mitigating drawbacks associated with both approaches. The static surface Gaussians and mesh vertices as well as the dynamic deformation network are learned via reference view photometric loss, score distillation loss as well as other regularization losses in a two-stage manner. Extensive experiments demonstrate that our method outperforms prior video-to-4D generation methods in terms of rendering quality and spatial-temporal consistency.

[NeurIPS '24] DreamMesh4D: Video-to-4D Generation with Sparse-Controlled Gaussian-Mesh Hybrid Representation Abstract (excerpt) We introduce DreamMesh4D, a novel framework that combines mesh representation with sparse-controlled deformation technique to generate high-quality 4D object from a monocular video. To overcome the limitation of classical texture representation, we bind Gaussian splats to the surface of the triangular mesh for differentiable optimization of both the texture and mesh vertices. In particular, DreamMesh4D begins with a coarse mesh provided by a single image based 3D generation method. Sparse points are then uniformly sampled across the surface of the mesh, and are used to build a deformation graph to drive the motion of the 3D object for the sake of computational efficiency and providing additional constraint. For each step, transformations of sparse control points are predicted using a deformation network, and the mesh vertices as well as the bound surface Gaussians are deformed via a geometric skinning algorithm. The skinning algorithm is a hybrid approach combining LBS (linear blending skinning) and DQS (dual-quaternion skinning), mitigating drawbacks associated with both approaches. The static surface Gaussians and mesh vertices as well as the dynamic deformation network are learned via reference view photometric loss, score distillation loss as well as other regularization losses in a two-stage manner. Extensive experiments demonstrate that our method outperforms prior video-to-4D generation methods in terms of rendering quality and spatial-temporal consistency.

MrNeRF

12,323 просмотров • 1 год назад

Virtual Textures in the Browser. This is a WebGL 2.0 implementation I did in 2023. The car model is from Sketchfab by Pavel Matoušek. It's a worst-case for virtual textures because the texture is generated from photogrametry software and has pathologically bad UV layout. The texture is 16,384 x 16,384 pixels, which is 180 Mb of PNG data. Loading this in Blender would crash Blender for me back then. The GPU memory requirement for this texture is 1 Gb. The VT displays the model after loading just 34 Kb (one tile). The other tiles are fetched in via a smart priority queue in the background as you move camera around the scene. The physical page texture is 2k, which is 16 times smaller than the source. The solution supports multiple separate virtual textures, and has GLTF integration. Texture filtering as well as anisotropy are fully supported as well. You can try the demo yourself here: Here's a writeup I did while working on this: The video recorded on a very crummy internet connection and I intentionally reload the page in the middle. The delay comes from the geometry download, actual texture part is near-instant.

Virtual Textures in the Browser. This is a WebGL 2.0 implementation I did in 2023. The car model is from Sketchfab by Pavel Matoušek. It's a worst-case for virtual textures because the texture is generated from photogrametry software and has pathologically bad UV layout. The texture is 16,384 x 16,384 pixels, which is 180 Mb of PNG data. Loading this in Blender would crash Blender for me back then. The GPU memory requirement for this texture is 1 Gb. The VT displays the model after loading just 34 Kb (one tile). The other tiles are fetched in via a smart priority queue in the background as you move camera around the scene. The physical page texture is 2k, which is 16 times smaller than the source. The solution supports multiple separate virtual textures, and has GLTF integration. Texture filtering as well as anisotropy are fully supported as well. You can try the demo yourself here: Here's a writeup I did while working on this: The video recorded on a very crummy internet connection and I intentionally reload the page in the middle. The delay comes from the geometry download, actual texture part is near-instant.

Alex Goldring

19,368 просмотров • 5 месяцев назад

Was working on CSM (Cascaded Shadow Maps) blending. My CSM implementation is a little unusual, I switch cascades as late as possible, using the highest available resolution cascade. Most CSM implementations choose cascades based on view depth, the problem with that is - you waste a lot of high resolution shadow texels, in my experience easily upwards of 50%. I figure - GPU already spent the effort to compute those shadow texels - why not use them, and get perceptually about 20-50% resolution increase in your shadows. This is not new, and MJP showed this in his code too (see below). The problem is in blending, if you use cascade projection matrix for choosing a cascade - blending becomes non-trivial. So I spent a lot of time working on that, and finally cracked it. Video shows blending of 5 cascades, the blend margin is exaggerated for demonstration purposes and cascades are pushed to the near plane for the same reason. The result is a perfect forward-only blend at the cost of a bit of ALU. Matt Pettineo is pretty much an authority on the subject nowadays, and I found his amazing repo very useful in the past:

Was working on CSM (Cascaded Shadow Maps) blending. My CSM implementation is a little unusual, I switch cascades as late as possible, using the highest available resolution cascade. Most CSM implementations choose cascades based on view depth, the problem with that is - you waste a lot of high resolution shadow texels, in my experience easily upwards of 50%. I figure - GPU already spent the effort to compute those shadow texels - why not use them, and get perceptually about 20-50% resolution increase in your shadows. This is not new, and MJP showed this in his code too (see below). The problem is in blending, if you use cascade projection matrix for choosing a cascade - blending becomes non-trivial. So I spent a lot of time working on that, and finally cracked it. Video shows blending of 5 cascades, the blend margin is exaggerated for demonstration purposes and cascades are pushed to the near plane for the same reason. The result is a perfect forward-only blend at the cost of a bit of ALU. Matt Pettineo is pretty much an authority on the subject nowadays, and I found his amazing repo very useful in the past:

Alex Goldring

18,775 просмотров • 5 месяцев назад

Vehicle-combat-game-dev-day 484: GPU instanced grass. Only one mesh for now, but the rendering system is robust and supports a LOT of instances and is fully procedural, generating grass on the fly! The game's levels are fully RNG & procedural #indiegamedev #solodev

Vehicle-combat-game-dev-day 484: GPU instanced grass. Only one mesh for now, but the rendering system is robust and supports a LOT of instances and is fully procedural, generating grass on the fly! The game's levels are fully RNG & procedural #indiegamedev #solodev

Jussi Kemppainen | Drivers of the Apocalypse

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Solo Through America's Wild West Coastline 🇺🇸 California's coastline is one of the most beautiful in the world. There is a section where the coastal HWY 1 goes inland and leaves a part of this rugged coastline and communities on their own. Join me today as we road trip through one of the most beautiful parts of the world and meet up with some fascinating locals who call it home.

Solo Through America's Wild West Coastline 🇺🇸 California's coastline is one of the most beautiful in the world. There is a section where the coastal HWY 1 goes inland and leaves a part of this rugged coastline and communities on their own. Join me today as we road trip through one of the most beautiful parts of the world and meet up with some fascinating locals who call it home.

Peter Santenello

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Hannatu: The fact that there is no arena that produces Afrobeats is quite a shame. That there is only one 5-star hotel in the capital of Nigeria, Abuja, the Hilltop Hotel, is also quite a shame. Abuja should have 5 or 6 world-class hotels, and we are working on about 3 of them in Abuja and 2 in Lagos.

Hannatu: The fact that there is no arena that produces Afrobeats is quite a shame. That there is only one 5-star hotel in the capital of Nigeria, Abuja, the Hilltop Hotel, is also quite a shame. Abuja should have 5 or 6 world-class hotels, and we are working on about 3 of them in Abuja and 2 in Lagos.

Imran Muhammad

195,409 просмотров • 4 месяцев назад

[SIGGRAPH '25] TeGA: Texture Space Gaussian Avatars for High-Resolution Dynamic Head Modeling Note: On the left that's a 3DGS rendering! Contributions: 1. We propose a simple approach for rigging 3D Gaussians within the continuous tangent space of 3DMM face models, allowing Gaussians to move freely across mesh triangles. 2. We propose a novel CNN-based deformation model that is agnostic to the number of 3D Gaussians, naturally enabling adaptively densification of the representation to improve detail where most needed, with expression-dependent shading. 3. We show significant improvements over baseline SOTA methods and demonstrate the ability to render even extreme close-up images at high quality.

[SIGGRAPH '25] TeGA: Texture Space Gaussian Avatars for High-Resolution Dynamic Head Modeling Note: On the left that's a 3DGS rendering! Contributions: 1. We propose a simple approach for rigging 3D Gaussians within the continuous tangent space of 3DMM face models, allowing Gaussians to move freely across mesh triangles. 2. We propose a novel CNN-based deformation model that is agnostic to the number of 3D Gaussians, naturally enabling adaptively densification of the representation to improve detail where most needed, with expression-dependent shading. 3. We show significant improvements over baseline SOTA methods and demonstrate the ability to render even extreme close-up images at high quality.

MrNeRF

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🚨 NOW: President Trump takes huge VICTORY LAP on the success of Space Force — which some Democrats MOCKED Space Force is now vastly improving the accuracy of our weapons on the ground. And we're leading China and Russia, easily 🔥 "I'm very proud of the Space Force because that was a branch that a new one that came up, and we were losing to Russia and to China in space." "Space Force is now leading the other countries, China, Russia, and there is no fourth, really, and leading them by, we saw numbers the other day, leading, we're leading in space by so much it's, we're never going to be caught. So I'm very proud of Space Force!" "I think it's going to be one of our most important as time goes by. A lot of the things that you see, a lot of the accuracy of the weapons is caused because of what we created with Space Force, so we're very proud of that."

🚨 NOW: President Trump takes huge VICTORY LAP on the success of Space Force — which some Democrats MOCKED Space Force is now vastly improving the accuracy of our weapons on the ground. And we're leading China and Russia, easily 🔥 "I'm very proud of the Space Force because that was a branch that a new one that came up, and we were losing to Russia and to China in space." "Space Force is now leading the other countries, China, Russia, and there is no fourth, really, and leading them by, we saw numbers the other day, leading, we're leading in space by so much it's, we're never going to be caught. So I'm very proud of Space Force!" "I think it's going to be one of our most important as time goes by. A lot of the things that you see, a lot of the accuracy of the weapons is caused because of what we created with Space Force, so we're very proud of that."

Eric Daugherty

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"The Promise" was written and recorded in a small garden shed turned into a studio at the home of vocalist Clive Farrington's father. The space was so tiny that they had to attach the keyboards vertically to the walls to fit everything! Released in 1988 as the debut single for When In Rome, it became #1 on the American Dance Chart, #1 on the Billboard Hot 100 and one of the biggest one-hit wonders of the 80s.

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CALL TO ACTIVISM

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