SRC3: A Video Dataset for Evaluating Domain Mismatch

Sato, Jonathan; Mediavilla, Chelsea; Ward, Chris M.; Parameswaran, Shibin

doi:10.1109/aipr47015.2019.9174589

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…The use of simulated data along with real data will improve overall detection quality. [23][24][25][26] For cooperative perception between agents most of the datasets rely on the use of gaming engines and simulations. 1,16 Wang et al 1 train V2VNet using simulated LIDAR from Manivasagam et al 19 Following suit with this work, Xu et al 27 have generated a publicly available platform where multiple cars can navigate one scene and generate data.…”

Section: Datasetsmentioning

confidence: 99%

Bandwidth constrained cooperative object detection in images

Marez

Nans²,

Borden³

2022

Artificial Intelligence and Machine Learning in Defense Applications IV

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Cooperative autonomous systems, such as swarms, multi-camera systems, or fleets of self-driving vehicles, can better understand a given scene by sharing multiple modalities and varying viewpoints. This superposition of data adds robustness and redundancy to a system typically burdened with obstructions and unrecognizable, distant objects. Collaborative perception is a key component of cooperative autonomous systems where modalities can include camera sensors, LiDAR, RADAR, and depth images. Meanwhile, the amount of useful information that can be shared between agents in a cooperative system is constrained by current communication technologies (e.g. bandwidth limitations). Recent developments in learned compression can enable the training of end-toend cooperative systems using deep learning with compressed communication in the pipeline. We explore the use of a deep learning object detector in a cooperative setting with a learned compression model facilitating communication between agents. To test our algorithm, this research will focus on object detection in the image domain as a proxy for one of the modalities used by collaborative systems.

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