Segmentation

Slides
Video Lecture

References

  1. Fully Convolutional Networks for Semantic SegmentationJonathan Long, Evan Shelhamer, Trevor Darrell2014
  2. Stacked Hourglass Networks for Human Pose EstimationAlejandro Newell, Kaiyu Yang, Jia Deng2016
  3. Depth Pro: Sharp Monocular Metric Depth in Less Than a SecondAleksei Bochkovskii, Amaël Delaunoy, Hugo Germain, Marcel Santos, Yichao Zhou, etal.2024
  4. The Cityscapes Dataset for Semantic Urban Scene UnderstandingMarius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, etal.2016
  5. Playing for Data: Ground Truth from Computer GamesStephan R. Richter, Vibhav Vineet, Stefan Roth, Vladlen Koltun2016
  6. Masked-attention Mask Transformer for Universal Image SegmentationBowen Cheng, Ishan Misra, Alexander G. Schwing, Alexander Kirillov, Rohit Girdhar2021
  7. Segment AnythingAlexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, etal.2023
  8. Mask R-CNNKaiming He, Georgia Gkioxari, Piotr Dollár, Ross Girshick2017
  9. The Mapillary Vistas Dataset for Semantic Understanding of Street ScenesGerhard Neuhold, Tobias Ollmann, Samuel Rota Bulo, Peter Kontschieder2017
  10. Free Supervision From Video GamesPhilipp Krähenbühl2018
  11. U-Net: Convolutional Networks for Biomedical Image SegmentationOlaf Ronneberger, Philipp Fischer, Thomas Brox2015