KITTI

KITTI Vision Benchmark Suite: We take advantage of our autonomous driving platform Annieway to develop novel challenging real-world computer vision benchmarks. Our tasks of interest are: stereo, optical flow, visual odometry, 3D object detection and 3D tracking. For this purpose, we equipped a standard station wagon with two high-resolution color and grayscale video cameras. Accurate ground truth is provided by a Velodyne laser scanner and a GPS localization system. Our datsets are captured by driving around the mid-size city of Karlsruhe, in rural areas and on highways. Up to 15 cars and 30 pedestrians are visible per image. Besides providing all data in raw format, we extract benchmarks for each task. For each of our benchmarks, we also provide an evaluation metric and this evaluation website. Preliminary experiments show that methods ranking high on established benchmarks such as Middlebury perform below average when being moved outside the laboratory to the real world. Our goal is to reduce this bias and complement existing benchmarks by providing real-world benchmarks with novel difficulties to the community.


References in zbMATH (referenced in 24 articles )

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  1. Marcos Nieto, Orti Senderos, Oihana Otaegui: Boosting AI applications: Labeling format for complex datasets (2021) not zbMATH
  2. Bredies, Kristian; Holler, Martin: Higher-order total variation approaches and generalisations (2020)
  3. Qin, Zixuan; Yin, Mengxiao; Li, Guiqing; Yang, Feng: SP-Flow: self-supervised optical flow correspondence point prediction for real-time SLAM (2020)
  4. Datta, Amitava; Kaur, Amardeep; Lauer, Tobias; Chabbouh, Sami: Exploiting multi-core and many-core parallelism for subspace clustering (2019)
  5. Holger Caesar, Varun Bankiti, Alex H. Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, Oscar Beijbom: nuScenes: A multimodal dataset for autonomous driving (2019) arXiv
  6. Jens Behley, Martin Garbade, Andres Milioto, Jan Quenzel, Sven Behnke, Cyrill Stachniss, Juergen Gall: SemanticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences (2019) arXiv
  7. Naiel, Mohamed A.; Ahmad, M. Omair; Swamy, M. N. S.: A vehicle detection scheme based on two-dimensional HOG features in the DFT and DCT domains (2019)
  8. Patil A., Malla S., Gang H., Chen Y.-T.: The H3D Dataset for Full-Surround 3D Multi-Object Detection and Tracking in Crowded Urban Scenes (2019) arXiv
  9. Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Sheng Zhao, Shuyang Cheng, Yu Zhang, Jonathon Shlens, Zhifeng Chen, Dragomir Anguelov: Scalability in Perception for Autonomous Driving: Waymo Open Dataset (2019) arXiv
  10. Lindeberg, Tony: Spatio-temporal scale selection in video data (2018)
  11. Xinyu Huang, Peng Wang, Xinjing Cheng, Dingfu Zhou, Qichuan Geng, Ruigang Yang: The ApolloScape Open Dataset for Autonomous Driving and its Application (2018) arXiv
  12. Berger, Johannes; Lenzen, Frank; Becker, Florian; Neufeld, Andreas; Schnörr, Christoph: Second-order recursive filtering on the rigid-motion Lie group (\mathrmSE_3) based on nonlinear observations (2017)
  13. Burger, Martin; Dirks, Hendrik; Frerking, Lena: On optical flow models for variational motion estimation (2017)
  14. Coninx, Alexandre; Bessière, Pierre; Droulez, Jacques: Quick and energy-efficient Bayesian computing of binocular disparity using stochastic digital signals (2017)
  15. Hollósi, Gergely; Lukovszki, Csaba; Moldován, István; Plósz, Sándor; Harasztos, Frigyes: Monocular indoor localization techniques for smartphones (2016)
  16. Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, Bernt Schiele: The Cityscapes Dataset for Semantic Urban Scene Understanding (2016) arXiv
  17. Xia, Shengxiang: A topological analysis on patches of optical flow (2016)
  18. Žbontar, Jure; Lecun, Yann: Stereo matching by training a convolutional neural network to compare image patches (2016)
  19. Buades, Antoni; Facciolo, Gabriele: Reliable multiscale and multiwindow stereo matching (2015)
  20. Demetz, Oliver; Hafner, David; Weickert, Joachim: Morphologically invariant matching of structures with the complete rank transform (2015)

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