Depth Estimation - 3.0 English

Vitis AI Library User Guide (UG1354)

Document ID
UG1354
Release Date
2023-01-12
Version
3.0 English

FADNet is a model used for depth estimation. It is a fast and accurate network for disparity estimation. It has three main features:

  1. It exploits efficient 2D-based correlation layers with stacked blocks to preserve fast computation.
  2. It combines the residual structures to make the deeper model easier to learn.
  3. It contains multiscale predictions to exploit a multiscale weight scheduling training technique to improve the accuracy.

The following images show the result of depth estimation. The first image is the left camera image input, the second image is the right camera image input and the third image is the running result of the FADNet model.

Figure 1. FADNet Depth Estimation Example





The following table lists the depth estimation models supported by the Vitis AI library.

Table 1. Depth Estimation Models
No Model Name Framework
1 FADNet_0_pt PyTorch
2 FADNet_1_pt
3 FADNet_2_pt
4 FADNet_v2_0_pt
5 FADNet_v2_1_pt
6 FADNet_v2_2_pt
7 FADNet_v2_pruned_0_pt
8 FADNet_v2_pruned_1_pt
9 FADNet_v2_pruned_2_pt