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Not Using the Car to See the Sidewalk — Quantifying and Controlling the Effects of Context in Classification and Segmentation
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Importance of visual context in scene understanding tasks is well recognized in the computer vision community. However, to what extent the computer vision models are dependent on the context to make their predictions is unclear. A model overly relying on context will fail when encountering objects in different contexts than in training data and hence it is important to identify these dependencies before we can deploy the models in the real-world. We propose a method to quantify the sensitivity
doi:10.1109/cvpr.2019.00841
dblp:conf/cvpr/ShettySF19
fatcat:xqwtlhuqqff3nk2xjzukfk6dmq