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Conference papers
BlitzNet: A Real-Time Deep Network for Scene Understanding
Abstract : Real-time scene understanding has become crucial in many applications such as autonomous driving. In this paper, we propose a deep architecture, called BlitzNet, that jointly performs object detection and semantic segmentation in one forward pass, allowing real-time computations. Besides the computational
gain of having a single network to perform several tasks, we show that object detection and semantic segmentation benefit from each other in terms of
accuracy. Experimental results for VOC and COCO datasets show state-of-the-art performance for object detection and segmentation among real time systems.
Cited literature [27 references]
https://hal.archives-ouvertes.fr/hal-01573361
Contributor : Nikita Dvornik <>
Submitted on : Wednesday, August 9, 2017 - 11:43:46 AM
Last modification on : Friday, April 17, 2020 - 11:16:02 AM
Contributor : Nikita Dvornik <>
Submitted on : Wednesday, August 9, 2017 - 11:43:46 AM
Last modification on : Friday, April 17, 2020 - 11:16:02 AM
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