Hi,
I am a newbie in te area of depth estimation using deep learning, so I apologize if my question seems naive.
I want to use the existing monodepth2 "pre-trained model" on KITTI to estimate the absolute distance. In this sense, I aim to do the inference on my "own dataset" (captured by my "GoPro camera") using this pre-trained model.
I am aware of the previous discussions here on the methods for generating absolute distance from the relative distance produced by the monodepth2 model.
However, I am wondering if it is possible to simply generate an absolute distance map from the relative distance map (produced using the pre-trained model KITTI) by solving a regression model by including the ground truth data (the absolute distance for several pixels on the depth map).
Something like (or other order of regression models):
Hi, I am a newbie in te area of depth estimation using deep learning, so I apologize if my question seems naive.
I want to use the existing monodepth2 "pre-trained model" on KITTI to estimate the absolute distance. In this sense, I aim to do the inference on my "own dataset" (captured by my "GoPro camera") using this pre-trained model.
I am aware of the previous discussions here on the methods for generating absolute distance from the relative distance produced by the monodepth2 model.
However, I am wondering if it is possible to simply generate an absolute distance map from the relative distance map (produced using the pre-trained model KITTI) by solving a regression model by including the ground truth data (the absolute distance for several pixels on the depth map).
Something like (or other order of regression models):
AbsoluteDistance= A*(ReltiveDistance)+B
Thank you!