Slvm
Pytorch implementation of 'A Biologically Inspired Separable Learning Vision Model for Real-time Traffic Object Perception in Dark'
Install / Use
/learn @alanli1997/SlvmREADME
A Biologically Inspired Separable Learning Vision Model for Real-time Traffic Object Perception in Dark
Dark-traffic benchmark
(object detection, instance segmentation, and optical flow estimation in the low-light traffic conditions)
images (~10k) and annotations (~100k) in Google Drive
The images are now available, and annotations will be released after the paper is processed by the journal/conference.
- 9.05 update: Available on Expert Systems with Applications, annotations (Detection/Segmentation/Flow) is released.
- 9.07 update: Code (SLVM for Static & Motion perception) is preparing to be released.
- 9.09 update: Code (SLVM for Motion perception) is released.
- 9.24 update: Code (SLVM for Static perception) is released.
SLVM for Det&Seg
training step coming soon...
SLVM for optical flow
Re-produce
python pip install -requirements.txt
References
- https://github.com/AlanLi1997/slim-neck-by-gsconv
- https://github.com/AlanLi1997/rethinking-fpn
- https://github.com/ultralytics/ultralytics
- https://github.com/haofeixu/gmflow
- https://github.com/neufieldrobotics/NeuFlow_v2
