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BiCross (Unsupervised Spike Depth Estimation via Cross-modality Cross-domain Knowledge Transfer).

Python 100.00%

cross-domain depth-estimation spike unsupervised

bicross-old's Introduction

Hello, I'm Qizhe Zhang!

English · 简体中文

About Me

I am currently a Ph.D. candidate at HMI Lab, NELVT, School of Computer Science, Peking University, advised by Prof. Shanghang Zhang. I received my Bachelor's degree in Artificial Intelligence (Turing Honor Class) from Peking University, where I also obtained a dual degree in Economics from National School of Development (NSD).

Research Interests

Computer Vision: Visual Foundation Models, Transfer Learning, Efficient Tuning, Continual Learning and Autonomous Driving.
Machine Learning: Contrastive Learning, Mixture of Experts, Sparse Training and Computational Neuroscience.

Research Projects

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Contact

📧Email: [email protected], [email protected]

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bicross-old's Issues

About dataset

Hi, nice work! Where can I download the dataset used in your paper?

Question about the eval_mask and uncertainty_head

Hi, I really thankful for you to share the code. In trainer_crossdomain.py the train function has set the
eval_mask[:, int(0.40810811 * height):int(0.99189189 * height), int(0.03594771 * width):int(0.96405229 * width)] = 1 and I wonder how to get the float numbers? Also, I noticed that the structures of uncertainty_head and head are nearly the same. I don't understand the reason for this similarity. Looking forward to the reply and appreciate for the paper, your idea is inspiring. Best.

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