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#rendering

2 posts2 participants0 posts today
Public
Douglas E. Welch

Lessons on How to Draw by Hokusai via Kottke [Shared]

In 1812, Japanese woodblock print artist Katsushika Hokusai, who would later become famous for his iconic Great Wave off Kanagawa prints, published a three-volume series called Quick Lessons in Simplified Drawing. All three volumes are available online: one, two, three. Even if you’re not in the market for drawing lessons, the pages are wonderful to flip through.

welchwrite.com/blog/2025/04/06

#art #drawing #education #rendering #lessons #Hokusai #artist #shared #books

@altbot

Public
Dudley Storey
"Midnight at the Museum"

Modelled and rendered in Blender. Something of an ongoing work in progress: in such compositions balancing light & dark and preserving details in shadow can be a long process.

#Blender #b3d #3drendering #Blender3D #blendercommunity #rendering #3d #3drender #render #blenderrender #cyclesrender #3dartwork #3dmodeling #3dart #digitalart #dinosaur #dinoart #dinosaurart #museum #dinosaurs #fossil #godrays
3D rendering of a posed T. Rex fossil, seen in profile in the middle of a museum at night, lit by light rays from above.
#godrays
Public
Dudley Storey
“Meganeura Trapped in Amber"

Recreation of an ancient insect in Blender. Related to dragonflies, Meganeura was one of the largest flying insects ever, with a wingspan of about 65–75 cm (2.13–2.46 ft). As such, it’s very unlikely that one would be captured by tree sap, so this portrays the animal in its nymph form.

#Blender #b3d #3drendering #Blender3D #blendercommunity #rendering #3d #3drender #render #blenderrender #cyclesrender #3dartwork #3dmodeling #3dart #digitalart #dragonfly #meganeua #ancientanimals #amber #permian
3D rendering of a dragonfly-like insect entombed in a chunk of amber.
#permian
Public
Paul Houle

🕶️ SeeLe: A Unified Acceleration Framework for Real-Time Gaussian Splatting

arxiv.org/abs/2503.05168

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arXiv.orgSeeLe: A Unified Acceleration Framework for Real-Time Gaussian Splatting3D Gaussian Splatting (3DGS) has become a crucial rendering technique for many real-time applications. However, the limited hardware resources on today's mobile platforms hinder these applications, as they struggle to achieve real-time performance. In this paper, we propose SeeLe, a general framework designed to accelerate the 3DGS pipeline for resource-constrained mobile devices. Specifically, we propose two GPU-oriented techniques: hybrid preprocessing and contribution-aware rasterization. Hybrid preprocessing alleviates the GPU compute and memory pressure by reducing the number of irrelevant Gaussians during rendering. The key is to combine our view-dependent scene representation with online filtering. Meanwhile, contribution-aware rasterization improves the GPU utilization at the rasterization stage by prioritizing Gaussians with high contributions while reducing computations for those with low contributions. Both techniques can be seamlessly integrated into existing 3DGS pipelines with minimal fine-tuning. Collectively, our framework achieves 2.6$\times$ speedup and 32.3\% model reduction while achieving superior rendering quality compared to existing methods.
#cs#graphics#software
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