Urban Scene Segmentation for Autonomous Vehicles using Multi-Domain Adaptation

Page 30

27

References [1] S.Kim, J.Philion, A.Torralba , S.Fidler, “DriveGAN: Towards a Controllable High-Quality Neural Simulation,” Computer Vision and Pattern Recognition ; Robotics, Apr 2021, Available: arXivLabs, https://arxiv.org/abs/2104.15060 . [Accessed November 2021]. [2]P.Mody, “List of Semantic Segmentation Models for Autonomous Vehicles,” playment.io,March. 6, 2018.[Online].Available:https://www.playment.io/blog/semantic-segmentation-models-autonomous-vehicles . [Accessed November 2021]. [3]C.Trivedi, “How to create realistic Grand Theft Auto 5 graphics with Deep Learning,” freeCodeCamp,August.1,2018.[Online].Available:https://www.freecodecamp.org/news/how-to-create-realisticgrand-theft-auto-5-graphics-with-deep-learning-cc092c4a69f0/. [Accessed November 2021]. [4] D.Mwiti, K.(Yi) Li, “Image Segmentation in 2021: Architectures, Losses, Datasets, and Frameworks,”neptune.ai,Dec.21,2021.[Online].Available:https://neptune.ai/blog/image-segmentation.[Accessed November 2021]. [5]T.Wang, M.Liu, J.Zhu, A.Tao, J.Kautz, B.Catanzaro, “High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs,” Computer Vision and Pattern Recognition; Graphics; Machine Learning, Nov 30, 2017 , Available: arXivLabs,https://arxiv.org/abs/1711.11585. [Accessed November 2021]. [6] J.Brownlee, “How to Develop a Conditional GAN (cGAN) From Scratch,”machinelearningmastery.com,September 1, 2020.[Online].Available:https://machinelearningmastery.com/how-to-develop-a-conditional-generativeadversarial-network-from-scratch/.[Accessed October 2021]. [7]G.Giacaglia,“HowTransformersWork,”towardsdatascience.com,Mar 11, 2019· .[Online].Available:https://towardsdatascience.com/transformers-141e32e69591.[Accessed November 2021]. [8]M.Phi, “Illustrated Guide to LSTM and GRU’s: A step by step explanation,”towardsdatascience.com, Sep 24, 2018. [Online]. Available:https://towardsdatascience.com/illustrated-guide-to-lstms-and-gru-s-a-step-bystep-explanation-44e9eb85bf21.[Accessed October 2021]. [9]V.Perez, “Transformers in Computer Vision: Farewell Convolutions!,”towardsdatascience.com, November 23, 2020. [Online]. Available:https://towardsdatascience.com/transformers-in-computer-vision-farewellconvolutions-f083da6ef8ab. [Accessed November 2021]. [10]A.Saporta, T.Hung, M.Cord, P.Perez, “Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation,” Computer Vision and Pattern Recognition ; Robotics, Apr 2021, Available: Valeo.ai, https://arxiv.org/pdf/2108.06962.pdf . [Accessed December 2021]. [11]S.Richter, V.Vineet, S.Roth, V.Koltun, “Playing for Data: Ground Truth from Computer Games,” Aug.7,2016,Available:paperswithcode.com,https://paperswithcode.com/paper/playing-for-data-ground-truthfrom-computer . [Accessed December 2021].

Urban Scene Segmentation for Autonomous Vehicles Using Multi-Domain Adaptation


Turn static files into dynamic content formats.

Create a flipbook
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.
Urban Scene Segmentation for Autonomous Vehicles using Multi-Domain Adaptation by mohamed elmesawy - Issuu