Context-based pedestrian path prediction. In Computer Vision-ECCV 2014, pages 618-633. Springer, 2014. 2J. Kooij, N. Schneider, F. Flohr, D. Gavrila, Context-based pedestrian path prediction, in: ECCV, 2014.J. Kooij, N. Schneider, F. Flohr, and D. M. Gavrila, "Context-based ...
Zhang P, Ouyang W, Zhang P, Xue J, Zheng N (2019) Sr-lstm: state refinement for lstm towards pedestrian trajectory prediction. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 12085–12094 LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521...
Evostgat: Evolving spatiotemporal graph attention net- works for pedestrian trajectory prediction. Neurocomputing, 491:333–342, 2022. [56] Makarand Tapaswi, Yukun Zhu, Rainer Stiefelhagen, Antonio Torralba, Raquel Urtasun, and Sanja Fidler. Movieqa: Understanding stories in movies through question-...
Like some research predicting vehicle [5] or pedestrian [6] motion trajectories, aircraft can be estimated based on their motion history. Their methods use the idea that the object is actively moving in most cases. However, aircraft in an apron does not drive fast due to their enormous size...
This field of view resulted in very low complexity and intra-class variance in GTOS (e.g., pedestrian’s feet were not observed in the image) compared to the higher view in MAGFRA-W and may reduce the prospects for generalizability to everyday terrains. Although there are 40 different ...
drawer, or scrollbar on a user interface, and the one or more secondary contextual views are selectable by a user; and in response to receiving a user input modifying the primary contextual view, modify one or more of the secondary contextual views based at least in part on the user input...
Gavrila, "Context-based pedes- trian path prediction," in European Conference on Computer Vision (ECCV), 2014, pp. 618-633.Kooij, J.F.P., Schneider, N., Flohr, F., Gavrila, D.M.: Context-based pedestrian path prediction. In: European Conference on Computer Vision. (2014) 618-633...
Context Model for Pedestrian Intention Prediction Using Factored Latent-Dynamic Conditional Random Fieldsdoi:10.1109/TITS.2020.2995166Satyajit NeogiMichael HoyKang DangHang YuJustin DauwelsInstitute of Electrical and Electronics Engineers (IEEE)
As mentioned in "Background", images in GTOS were collected while the camera-ground distance is much smaller than the height of the waist-mounted camera. This field of view resulted in very low complexity and intra-class variance in GTOS (e.g., pedestrian’s feet were not observed in th...
Gavrila, „Context-based pedestrian path prediction," in Computer Vision - ECCV 2014, Zurich, Switzerland, 2014, p. 618-633.J. F. P. Kooij, N. Schneider, F. Flohr, and D. M. Gavrila. Context-based pedestrian path prediction. In Computer Vi- sion - ECCV 2014 - 13th ...