Meeting date: 07-06-2023 (9h30)
Object detection
All YOLO versions
Lane detection
https://paperswithcode.com/sota/lane-detection-on-culane
→ https://github.com/Turoad/lanedet (output isn’t segmentation)
→ (CLRNet) https://arxiv.org/pdf/2305.08366v1.pdf
Enet-SAD (SCNN detector)
https://arxiv.org/pdf/1908.00821.pdf
https://github.com/InhwanBae/ENet-SAD_Pytorch - No pre-trained model
https://github.com/cardwing/Codes-for-Lane-Detection
https://drive.google.com/file/d/1-E0Bws7-v35vOVfqEXDTJdfovUTQ2sf5/view?pli=1
LaneNet
https://arxiv.org/pdf/1807.01726v1.pdf
https://github.com/klintan/pytorch-lanenet
https://github.com/IvanVassi/LaneNet-with-homography - No pre-trained model
https://github.com/Turoad/lanedet - different kinds of detectors and pre-trained models
Semantic segmentation
Enet (multiple classes)
https://arxiv.org/pdf/1606.02147.pdf
https://github.com/gjy3035/enet.pytorch
https://github.com/davidtvs/PyTorch-ENet/ - already implemented
EspNet
https://github.com/sacmehta/ESPNet
EdgeNet (only drivable area (and uses multi-task learning techniques))
https://ieeexplore.ieee.org/document/8951276
Can’t find any implementation
Car detection + Lane detection + Drivable area
YOLOP
YOLOPv2 (previously done)
HybridNet
https://arxiv.org/pdf/2203.09035.pdf
https://github.com/datvuthanh/HybridNets
Object deteciton + Semantic segmentation