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CVLAB-Unibo / Learning2AdaptForStereo

Code for: "Learning To Adapt For Stereo" accepted at CVPR2019
Apache License 2.0
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Question about the pretrained weights #8

Open Tiam2Y opened 2 years ago

Tiam2Y commented 2 years ago

Hello! Thanks for the great work! @AlessioTonioni But I have some questions about pretrained weights.

The pretrained weights you provide are exactly the same as the weights in this repository (Real-time-self-adaptive-deep-stereo). So how do I get the weights pretrained on Carla or synthia (with meta learning)?

AlessioTonioni commented 2 years ago

Hi, unfortunatelly I don't have these weights anymore. The code provided covers all the training and pretraining phases so it should be possible to retrain the network on your own if needed.

Tiam2Y commented 2 years ago

Well, thanks for your answer and code! @AlessioTonioni In order to train the weights of L2A+Wad, there are still several problems, as follows:

  1. Is the Synthia dataset you used before from this link? http://synthia-dataset.net/downloads/ datasets

  2. This dataset provides the ground-truth of depth. In order to obtain the ground-truth of disparity, is it converted according to the following calibration information after decoding the depth value? (Like converting the depth value of KITTI Raw data?) calib_kitti calibration file on KITTI format. P0, P1, P2, P3 corresponds to the same intrinsic camera matrix.

In order to express question 2 more clearly, take the calibration file calib_cam_to_cam.txt in KITTI Raw data 2011_09_30_calibas an example, assuming that the depth is known, is the disparity calculated by the following formula? depth2disp

标定文件

Sorry for the troublesome questions, but I'd appreciate your answers!

AlessioTonioni commented 2 years ago

Hello,

  1. We used the Synthia Video Sequences images from the link you provided above.
  2. disparity = (focal*baseline)/depth, you can get baseline and focal of the camera system from the camera calibration files in every dataset. Remember to express baseline and depth in the same unit of measure (e.g., both in meters).
Tiam2Y commented 2 years ago

All right, I got it. Thanks a lot!