2 code implementations • CVPR 2022 • Dongkwon Jin, Wonhui Park, Seong-Gyun Jeong, Heeyeon Kwon, Chang-Su Kim
Second, we generate a set of lane candidates by clustering the training lanes in the eigenlane space.
Ranked #29 on Lane Detection on TuSimple
1 code implementation • 25 Sep 2019 • Andrew Hundt, Benjamin Killeen, Nicholas Greene, Hongtao Wu, Heeyeon Kwon, Chris Paxton, Gregory D. Hager
We are able to create real stacks in 100% of trials with 61% efficiency and real rows in 100% of trials with 59% efficiency by directly loading the simulation-trained model on the real robot with no additional real-world fine-tuning.