Windfoil is a GPU-friendly algorithm that unifies rasterisation and differentiable vector graphics by evaluating the box-filtered winding number of quadratic Bézier contours in closed form. Implemented in WebGPU, it runs across diverse environments—from web browsers on consumer laptops to high-resolution print media—and supports real-time 2D rendering, high‑resolution rasterisation, and differentiable rendering. Compared to production engines like Skia and game‑oriented rasterisers such as Slug, Windfoil achieves closer fidelity to a reference coverage while maintaining comparable performance, and it outperforms DiffVG and Bézier Splatting in reconstruction quality at a fraction of the per‑step cost, scaling to tens of thousands of shapes at interactive rates.
arXiv:2609.06157v1 Announce Type: cross Abstract: 3D Gaussian splatting (3DGS) represents scenes with explicit primitives and supports real-time novel-view synthesis, yet its system efficiency varies...
MeshSplatBench is the first benchmark designed to evaluate triangle- and mesh-based neural rendering methods from native rendering to deployment in graphics engines such as Unity and Blender. It introduces a hierarchical deployment protocol with standard and dedicated options, and a structural audit for mesh splatting to assess topological and geometric integrity. The benchmark’s evaluations show that graphics engine deployment degrades quality, dedicated deployment preserves fidelity at a significant speed cost, and current mesh splatting methods lack sufficient connectivity for manifoldness.
arXiv:2607. 17842v1 Announce Type: cross Abstract: Recent breakthroughs in 3D Gaussian Splatting (3DGS) have advanced neural rendering with high fidelity and speed.
arXiv:2609.01306v1 Announce Type: cross Abstract: Triangle-based neural rendering bridges neural scene representations and conventional graphics pipelines by optimizing explicit geometric primitives...
arXiv:2608.20803v1 Announce Type: cross Abstract: Vector graphics are prized for their resolution independence, compact storage, and direct editability, making differentiable optimization of their pa...
arXiv:2606. 30292v1 Announce Type: new Abstract: We present DreamForge-World 0.
arXiv:2506. 07069v2 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, combining high-quality reconstruction with efficient rendering.
arXiv:2606. 31764v2 Announce Type: replace-cross Abstract: Differentiable rendering of planar rational splines remains largely underexplored, despite their widespread use in vector graphics and design.
arXiv:2609.23380v1 Announce Type: new Abstract: Gaussian Splatting has enabled real-time novel view synthesis, but its tightly coupled geometry and appearance representation often require a large num...
arXiv:2608. 13255v1 Announce Type: cross Abstract: Geometry-conditioned multi-view diffusion enables high-quality 3D texture generation, but its repeated per-view denoiser evaluations introduce substantial computational cost.
The paper presents memory‑efficient GPU pipelines that accelerate real‑time non‑line‑of‑sight (NLOS) reconstruction. By redesigning two wave‑based algorithms—f‑k migration and phasor‑fields—with fused kernels, warp‑level photon binning, batched transforms, CUDA graph replay, and selective FP16 storage, the authors achieve up to 42× speed‑ups over a reference streaming pipeline and 14× over the fastest published GPU baseline while reducing memory usage to as little as 2.5%. The work also includes an ablation study of implementation choices and introduces three denoising strategies that leverage the increased frame budget for future NLOS video processing.
The paper introduces a compact neural appearance model for 3D Gaussian Splatting that replaces traditional low‑order spherical harmonics (SH) with a tiny shared MLP decoding per‑primitive latent codes. It compares SH with recent spherical appearance models, integrating all into a unified CUDA rasterizer and WebGL viewer, and demonstrates that the new neural representation reduces per‑primitive appearance storage from 192 to 28 bytes, speeds optimization by 1.3×, and improves reconstruction quality. The study also analyzes how different appearance parametrizations affect geometry recovery and the handling of non‑static scene content.