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Basically we use self-supervised methods to train depth prediction models. Have you tried self-supervised combined with supervised methods? You know, Nuscenes and DDAD datasets have some sparse point…
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Hi,
Training the self supervised model from scratch takes a lot of time on 1 GPU machine. For the data that I have, it takes ~8hrs to train for 1 epoch.
Apart from increasing the GPU count, do w…
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Hello, thank you for your outstanding work. I noticed that this is a self supervised method that is very suitable for real-world scenarios. A total of three datasets were used for evaluation, with Ev …
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Hello,
Thank you for your work on P2C, and for sharing the code. You really did an excellent job!
I have some questions regarding the implementation of the unsupervised method (P2C*) mentioned …
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Hello, I had the pleasure of reading your article and found it valuable. I would like to ask if you could kindly share the source code? Even a partial portion of the code would be appreciated.
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The basic idea and methodology of CutAddPaste are highly similar to the ICLR23 paper AnomalyBERT [1]. However, there is no reference to AnomalyBERT and I can't find any discussion regarding the differ…
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**Home Assistant Setup**
Please indicate your version of HA and how it is installed.
Version: 2024.11.2
Installation Type (put an X between the square brackets for your HA):
[x] Home Assistant…
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The accuracy and robustness of the selection of key points seems to be crucial, which depend on "Self-supervised Pretraining"
However, this step needs "a single subject and its set of **aligned** d…
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@yaringal
Thank you for your example, it helps a lot to understand the paper. I am currently use the proposed formula (exp(-log_var)*loss+log_var)) in self-supervised learning with uncertainty…
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[Self-Supervised Sparse-to-Dense: Self-Supervised Depth Completion from LiDAR and Monocular Camera](https://ieeexplore.ieee.org/abstract/document/8793637)