Learning Adaptive Gaussian Sampling for 3D Generation: Density‑Sampled Gaussians (DeG) at SIGGRAPH 2026

The SIGGRAPH 2026 paper “Generative 3D Gaussians with Learned Density Control” introduces Density‑Sampled Gaussians (DeG), a differentiable framework that lets a model learn where to place Gaussian splats by sampling from a learned spatial density, enabling arbitrary‑budget, non‑uniform 3D representations with higher quality per cost.

3D Gaussian SplattingAdaptive SamplingDifferentiable Rendering

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Learning Adaptive Gaussian Sampling for 3D Generation: Density‑Sampled Gaussians (DeG) at SIGGRAPH 2026

Machine Heart

May 7, 2026 · Artificial Intelligence

Photo‑Level Simulation Bridges Vision Gap for Robot Learning (GS‑Playground, RSS 2026)

GS‑Playground is a next‑generation visual‑high‑fidelity robot simulator that cuts photo‑level rendering cost, automates asset creation, and narrows the Sim2Real gap, achieving up to 10,000 FPS on RTX 4090 and outperforming MuJoCo by 32× while supporting full‑stack parallel physics, 3DGS rendering, and end‑to‑end Real2Sim pipelines.

3D Gaussian SplattingHigh ThroughputSimulation

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Photo‑Level Simulation Bridges Vision Gap for Robot Learning (GS‑Playground, RSS 2026)

Machine Heart

Apr 8, 2026 · Artificial Intelligence

From a Single Image to a Physically Realistic 4D Video in One Minute

PhysGM, a CVPR 2026 paper by Beijing Institute of Technology and Li Auto, transforms a single static image into a high‑fidelity 4D video that obeys real‑world physics in under a minute, using a dual‑decoder transformer, DPO alignment, and a newly built 50k‑item PhysAssets dataset, outperforming prior methods in speed and quality.

3D Gaussian SplattingCVPR 2026Direct Preference Optimization

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From a Single Image to a Physically Realistic 4D Video in One Minute

Xiaomi Tech

Nov 28, 2025 · Artificial Intelligence

Xiaomi Auto Team Wins ICCV 2025 RealADSim Challenge with 3D Gaussian Splatting

The Xiaomi automotive research team secured first place in the ICCV 2025 RealADSim New View Synthesis challenge by presenting a four‑stage, 3D Gaussian Splatting‑based pipeline that tackles LiDAR‑free initialization, structured road modeling, generative pseudo‑ground‑truth refinement, and time‑invariant adaptation, achieving top PSNR, SSIM, and LPIPS scores.

3D Gaussian SplattingAutonomous Driving SimulationICCV 2025

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Xiaomi Auto Team Wins ICCV 2025 RealADSim Challenge with 3D Gaussian Splatting