uzh-rpg / event-based_vision_resources Goto Github PK

Paper: https://arxiv.org/abs/2108.05015

Project: https://sites.google.com/view/viseventtrack/

Hi, When I clicked the link for Hillhouse Technology in 'Companies working on Event-based Vision', I reached to a blog that seems irrelevant to event-based cameras. (I know Japanese and the blog is for something very inappropriate... lol)

I believe that the domain for Hill house Technology has been expired and that domain has been taken by someone else.

I think it's better to be fixed. Thank you!

Hi，Please tell me how to get the timestamp with DVS240C connectting To FPGA by CAVIR cable？
this cable is 40 line. Please provide more detail information. thanks

The DDD20 (previously DDD17+) is published at:

• Hu, Y., Binas, J., Neil, D., Liu, S.-C., and Delbruck, T. (2020). "DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction". Special session Beyond Traditional Sensing for Intelligent Transportation, The 23rd IEEE International Conference on Intelligent Transportation Systems, September 20 – 23, 2020, Rhodes, Greece. arXiv [cs.CV]. arXiv. http://arxiv.org/abs/2005.08605

Can you add this to the list? Thank you very much in advance!

Regards,
Yuhuang.

Can you add this work? https://openaccess.thecvf.com/content/CVPR2022/html/Plizzari_E2GOMOTION_Motion_Augmented_Event_Stream_for_Egocentric_Action_Recognition_CVPR_2022_paper.html

It is N-EPIC-Kitchens, the first event-based camera extension of the large-scale EPIC-Kitchens dataset.

Hello sirs. Thank you for your great work.

Is there any information about speck at : https://www.speck.ai/ .
The camera itself look like and event-based camera.
So i think you should add it into your page.

Hi, I have added my recent paper on 'Moving Object Detection for Event-based Vision using Graph Spectral Clustering', accepted in the ICCVW 2021. I have created a pull request for the same.

Hi,

Someone asks me if the DDD17 dataset has any optical flow ground truth/computed optical flow.
As I can recall, DDD17 has APS, DVS events, and car control signal.
Can you make a correction in this section: https://github.com/uzh-rpg/event-based_vision_resources#optical-flow

Regards,
Yuhuang.

My understanding is that the Visual Odometry is a Ego-Motion (also called Camera Motion).
Is there a misunderstanding in my understanding?

Hi, thanks for this nice resource list.

I'm look for Dr. Henri Rebecq's PhD dissertation, "Event Cameras, from SLAM to High Speed Video",
but cannot find this on "Dissertation" catalog or anywhere else.
So could you please provide a link to this?

Thanks so much.

I am trying to convert event data to image intensities. I have found several algorithms that do so like:

1. Image Reconstruction for Event Cameras Using Manifold Regularization.
2. Events-to-Video: Bringing Modern Computer Vision to Event Cameras
3. Simultaneous Optical Flow and Intensity Estimation from an Event Camera

I have two questions,

1. Is there a framework/tool-chain for these algorithm, in python or open-cv or any out of the box framework. (I am trying to implement the git hub code provided in the above mentioned paper as of now)

2. Is there a simple algorithm for me to use, other than the above listed one. Like simple integration or sliding window one. Can someone point me to the code/papers which do so.

With regards,
sameer

Zhu et. al. CVPR 2019,
Unsupervised Event-Based Learning of Optical Flow, Depth, and Egomotion.

I belive you intending add links to the paper while you have added it to the author.

Everything is there now but navigating to or linking to these two separate things is not possible now. Can I attempt to split them into two major sections?