Thank you for the talk! It was really clear, easy to understand and inspiring. It's amazing to see how self-supervised training leverages deep learning over human intuition.
@martinschulze53992 жыл бұрын
Im rather new to the field of neural SLAM (more experience with spiking neural networks etc.) and have given out a master thesis on visual SLAM on graph NNs to get me on track ASAP and your work is one of the top ones on my interest list. Good job and thanks ;)
@TomaszMalisiewicz2 жыл бұрын
Hi Martin, Thanks for the kind words! I'm glad that by making my team's papers and this talk publicly available, others can learn about all of this exciting work.
@darrenruben2981 Жыл бұрын
Keep making pmhs proud
@finkelmann2 жыл бұрын
Great presentation - super interesting, and very eloquent and clear.
@amortalbeing2 жыл бұрын
Loved it. Thanks a lot. you are really very good at presenting this.
@rashikshrestha18474 жыл бұрын
Thank you for the talk Tomasz Malisiewicz. Can we train SuperGlue to match ORB features ? How much effective might be the result ?
@TomaszMalisiewicz3 жыл бұрын
Yes, you can train a SuperGlue variant to work with whatever features you want. We evaluated two variants in our SuperGlue paper -- one network was trained to work with SuperPoint features and the other network was trained with SIFT features. You can make SuperGlue work with just about any descriptor you want, but keep in mind that ORB was designed to be lean and fast while deep networks are much slower and bigger.
@James_Albert Жыл бұрын
Hi @Tom Thank you for the fantastic presntation! I want to play with your code, but access was denied
@TomaszMalisiewicz4 жыл бұрын
If you want to watch the 5-minute video about our "SuperGlue: Learning Feature Matching with Graph Neural Networks" CVPR2020 paper, go here: kzbin.info/www/bejne/eH_Eenp_abuhma8
@jandresjn3 жыл бұрын
Hi, I'm now a fan of your research. I plan to carry out my master's research project on how to optimize these "feature matching" processes or stages where I can apply deep-learning to improve the Slam technique. I would like to know what are the main problems you have had.
@TomaszMalisiewicz3 жыл бұрын
It's been pretty difficult to get quantities like camera pose (Rotation and translation) to be the output of a deep neural network. It's pretty easy to turn keypoint identification and matching into a deep network. There are lots of interesting problems at the intersection of Deep Learning and SLAM. Good luck with your research!
@jandresjn3 жыл бұрын
@@TomaszMalisiewicz Thank you for the answer. Actually, i am going to focus on the pose problem with a deep network, I hope to be able to contribute something in the future, since I am at the beginning of the master, but I already had experience with SFM in the undergraduate. Regards!