I'm working on collecting and annotating data with a stereo camera for pedestrian detection and for accelerating the annotation process, I was thinking about using an already trained algorithm for generating annotation boxes proposals and as Stereo-RCNN is on top of the list for Kitti vehicle detection benchmark, wanted to ask if you already tested Stereo-RCNN for pedestrian detection and would it be much overhead/worth it to train it for pedestrian detection.
This work may not work very well for pedestrian, because we use a "box-shape" to model the object shape. As we mentioned in the paper, this issue can be addressed by leaning general object shape.
Hi,
I'm working on collecting and annotating data with a stereo camera for pedestrian detection and for accelerating the annotation process, I was thinking about using an already trained algorithm for generating annotation boxes proposals and as Stereo-RCNN is on top of the list for Kitti vehicle detection benchmark, wanted to ask if you already tested Stereo-RCNN for pedestrian detection and would it be much overhead/worth it to train it for pedestrian detection.
Best regards, Amine