Depth Modes

StereoLabs AI Depth leverages advanced neural networks to generate high-quality depth maps from stereo images, delivering reliable results even in challenging scenarios. Compared to traditional approaches, AI Depth provides superior accuracy in low-texture and low-light environments. This makes it especially well-suited for applications such as robotics, augmented reality (AR), and 3D mapping, where dependable depth perception is critical.

The ZED SDK provides multiple AI-powered depth modes, allowing you to tailor depth sensing to your application’s requirements. Each mode offers a different balance of accuracy, range, and computational speed, so you can optimize for precision, performance, or a mix of both depending on your use case.

Which depth mode should I use?

The three neural modes described below are the ones to choose between in ZED SDK v5. The legacy PERFORMANCE, QUALITY, and ULTRA modes are still available in the API but are deprecated in favor of them. Two other values of DEPTH_MODE are not depth modes in the same sense: NONE disables depth computation entirely, and CUSTOM lets you feed the SDK your own disparity or depth estimation (see the custom depth ingestion sample).

NEURAL

The NEURAL depth mode uses AI-powered disparity estimation to deliver a strong balance of depth accuracy and processing speed. It is ideal for applications that require reliable depth perception without sacrificing real-time performance.

NEURAL is also the only depth mode that supports INT8 inference precision, which trades a small amount of accuracy for faster, lower-memory depth computation. See Depth Precision.

Neural Depth Computational Performance on embedded devices

Neural Depth Accuracy (ZED X)

(*) A lower standard deviation indicates more stable and accurate depth estimation, resulting in smoother and more reliable 3D point clouds. Higher deviation can lead to noise and distortion, producing wavy or unstable point clouds.

Enabling the NEURAL depth mode in the API

// Set depth mode in NEURAL
InitParameters init_parameters;
init_parameters.depth_mode = DEPTH_MODE::NEURAL;

NEURAL LIGHT

The NEURAL_LIGHT depth mode provides AI-powered disparity estimation optimized for speed and efficiency. It enables real-time depth sensing with lower computational load, making it ideal for multi-camera setups and applications where fast processing is prioritized over maximum depth accuracy.

Neural Light Depth Computational Performance on embedded devices

Neural Light Depth Accuracy (ZED X)

(*) A lower standard deviation indicates more stable and accurate depth estimation, resulting in smoother and more reliable 3D point clouds. Higher deviation can lead to noise and distortion, producing wavy or unstable point clouds.

Enabling the NEURAL LIGHT depth mode in the API

// Set depth mode in NEURAL_LIGHT
InitParameters init_parameters;
init_parameters.depth_mode = DEPTH_MODE::NEURAL_LIGHT;

NEURAL PLUS

The NEURAL_PLUS depth mode provides the highest depth accuracy and detail among all AI-powered modes. It is designed for applications that demand maximum precision and robustness, such as advanced robotics, inspection, and 3D reconstruction. While it requires more computational resources and delivers lower frame rates compared to other modes, NEURAL_PLUS excels in challenging environments and when capturing fine object details is critical.

Neural Plus Depth Computational Performance on embedded devices

Neural Plus Accuracy (ZED X)

(*) A lower standard deviation indicates more stable and accurate depth estimation, resulting in smoother and more reliable 3D point clouds. Higher deviation can lead to noise and distortion, producing wavy or unstable point clouds.

Enabling the NEURAL PLUS depth mode in the API

// Set depth mode in NEURAL_PLUS
InitParameters init_parameters;
init_parameters.depth_mode = DEPTH_MODE::NEURAL_PLUS;

Depth Modes Comparison

Note:

• The depth range is highly dependent on the camera baseline and optics. A bigger baseline increases the maximum depth range but also raises the minimum working distance, while a smaller baseline does the opposite. Here, tests were conducted with a ZED X (lens of 2 mm) whose stereo baseline is 120 mm.
• Jetson Power Profile: Tests were conducted using MAXN without Super mode.