# Visualization and Labeling of Point Clouds in Virtual Reality

arXiv: https://arxiv.org/abs/1804.04111 · HTML: https://mlsanity.com/paper/1804.04111/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Apr 2018.

## Built on by (most cited first, 6 of 6)

- [SSPU-Net: Self-Supervised Point Cloud Upsampling via Differentiable Rendering](https://mlsanity.com/paper/2108.00454/) (2021)
- [Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalability](https://mlsanity.com/paper/2402.12225/) (2024)
- [3DVerifier: Efficient Robustness Verification for 3D Point Cloud Models](https://mlsanity.com/paper/2207.07539/) (2022)
- [Rendering-Oriented 3D Point Cloud Attribute Compression using Sparse Tensor-based Transformer](https://mlsanity.com/paper/2411.07899/) (2024)
- [Learning Versatile 3D Shape Generation with Improved AR Models](https://mlsanity.com/paper/2303.14700/) (2023)
- [FractalCloud: A Fractal-Inspired Architecture for Efficient Large-Scale Point Cloud Processing](https://mlsanity.com/paper/2511.07665/) (2025)

## Abstract (arXiv)

We present a Virtual Reality (VR) application for labeling and handling point cloud data sets. A series of room-scale point clouds are recorded as a video sequence using a Microsoft Kinect. The data can be played and paused, and frames can be skipped just like in a video player. The user can walk around and inspect the data while it is playing or paused. Using the tracked hand-held controller, the user can select and label individual parts of the point cloud. The points are highlighted with a color when they are labeled. With a tracking algorithm, the labeled points can be tracked from frame to frame to ease the labeling process. Our sample data is an RGB point cloud recording of two people juggling with pins. Here, the user can select and label, for example, the juggler pins as shown in Figure 1. Each juggler pin is labeled with various colors to indicate di erent labels.