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Unisim

This is an unofficial re-implementation of UniSim: A Neural Closed-Loop Sensor Simulator.

Installation

This is a plugin to neurad-studio. Please refer to the neurad-studio documentation for information about prerequisites and dependencies before the installation of this plugin.

If you wish to develop on this plugin, simply clone the repository and install neurad-studio:

pip install git+https://github.com/georghess/neurad-studio.git
pip install -e .

If you just want to run UniSim in your existing neurad-studio environment, you can run it directly as any other method using the ns-train command:

ns-train unisim pandaset-data --data data/pandaset

and follow the instructions in the terminal.

Usage

ns-train unisim pandaset-data --data data/pandaset

Models

We provide a unisim model, which is our attempt at a faithful reimplementation. Note that the GAN loss is disabled by default, as there was a large degree of uncertainty in its implementation. We especially welcome any contributions in this area.

We also provide a unisim++ model, which includes a number of tweaks/changes to the original model. These include:

• Enabling various improvements from NeuRAD, such as rolling shutter compensation and training with missing lidar points.
• Using a mipnerf-style gaussian approximation to compensate for the spatial extent of frustums.
• Replacing the first stage of unisim training with a learning rate warmup.
• Tuned losses and hyperparameters.