Abstract: This paper proposes a method for learning 3D semantic segmentation robust to incomplete point clouds. Our method first generates pseud-incomplete point clouds from original 3D point clouds ...

UniPre3D is the first unified pre-training method for 3D point clouds that effectively handles both object- and scene-level data through cross-modal Gaussian splatting. Our proposed pre-training task ...

Adverse weather conditions such as snow, fog, and rain pose significant challenges to LiDAR-based perception models by introducing noise and corrupting point cloud measurements. To address this issue, ...

The Pixel 10 lineup may not turn heads with its familiar design, but under the hood, it delivers major upgrades—more powerful performance, enhanced cameras, and cutting-edge AI—all at the same price ...

A new survey by Google Cloud and The Harris Poll has found that 87% of developers are using AI agents in their workflows. The research survey, published on August 18, 2025, was conducted in late June ...

Abstract: Existing point cloud completion methods, which typically depend on predefined synthetic training datasets, encounter significant challenges when applied to out-of-distribution, real-world ...