4 ms·
Faster R-CNN: Down the rabbit hole of modern object detection
- rambossa 9y agoDoes anyone try to get accurate bounding boxes (rotation, correct angle) with these object detection models? Or does the greatly harden the problem?
- electrograv 9y agoThat’s exactly what Faster-RCNN does. Edit: Except for rotation — they are axis aligned bounding boxes. Mask-RCNN (more recent) takes it a step further and also generates a per-object pixel segmentation mask, which is even better than a bounding box obviously. For that reason, Mask-RCNN is much more exciting to me, and incredibly impressive if you see examples showing what it can do. That said, “under the hood” of Mask-RCNN are still axis aligned 2D bounding boxes for every object (and this occasionally creates artifacts when a box is erroneously too small and crops off part of an object). IMO we need to somehow get away from these AABBs, but right now methods that use them simply work the best.
- nnq 9y agowansn't R-CNN already superseded by YOLO[1]? didn't read the article, but no mention of it to compare itself to, so seems outdated maybe. anyone had the time to dig deeper into this? [1] https://pjreddie.com/media/files/papers/yolo.pdf https://pjreddie.com/media/files/papers/yolo.pdf
- BillyParadise 9y agoIs this what they use for self driving cars?
- bitL 9y agoFaster R-CNN gives you only like 5fps on high-end GPU, so answer is no.
- nicodjimenez 9y agoObject detection is an interesting failure for deep learning. Systems such as these perform well but whenever you have something like non max suppression at the end you are bound to get hard to fix errors. I'm more optimistic about deep mask and similar pixel wise approaches as well as using RNNs to generate a list of objects from an image.
- swframe2 9y agoI saw this today: https://github.com/facebookresearch/Detectron https://github.com/facebookresearch/Detectron