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Towards Effective and Efficient 3D V...

Hong, Ziyang,

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Towards Effective and Efficient 3D Visual Perception /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Towards Effective and Efficient 3D Visual Perception // Ziyang Hong.
作者:	Hong, Ziyang,
面頁冊數:	1 electronic resource (102 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-05, Section: B.
Contained By:	Dissertations Abstracts International86-05B.
標題:	Computer engineering. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31718291
ISBN:	9798346544227

Towards Effective and Efficient 3D Visual Perception /
Hong, Ziyang,

Towards Effective and Efficient 3D Visual Perception /Ziyang Hong. - 1 electronic resource (102 pages)

Source: Dissertations Abstracts International, Volume: 86-05, Section: B.

We are witnessing developments in artificial intelligence (AI), where the most relevant parts to us are embodied AI systems with robotic agents interacting with human users in real-world environments. To serve in the embodied AI system, the agent robots need visual intelligence, namely the three-dimensional (3D) perception of the surrounding envi ronment. This thesis is dedicated to enabling real-time low-cost edge deployment of visual perception which is advocated by us as the future solution for embodied AI applications.First, an end-to-end deep neural network pipeline for machinery visual perception, CDRNet, is proposed. It jointly perceives a 3D scene's geometry structure and semantic labels. While conventional volumetric approaches for 3D perception tend to focus on the global coherence of their reconstructions, which leads to a lack of local geometric detail, CDRNet leverages the latent geometric prior knowledge in 2D image features by explicit depth prediction and anchored feature generation, to refine the occupancy learning in TSDF volume.Besides, we find that this cross-dimensional feature refinement methodology can also be adopted for the semantic segmentation task by utilizing semantic priors, to extract both 3D mesh and 3D semantic labeling in real-time. Beyond public datasets for test ing, we further implement a real-time messaging system to support these aforementioned perception tasks in real-life scenarios.Finally, a software-hardware co-optimization system, Efficient-Grad is proposed to enable the online AI model fine-tuning. It improves both throughput and energy saving with negligible accuracy degradation during model training for deep convolutional neural networks, by utilizing sparsity and asymmetry residing in the gradients for conventional back propagation. Furthermore, the dedicated hardware architecture for sparsity utiliza tion and efficient data movement is optimized to support the Efficient-Grad algorithm in a scalable manner, which leads to its superiority in terms of energy efficiency.

English

ISBN: 9798346544227Subjects--Topical Terms:

621879
Computer engineering.

Towards Effective and Efficient 3D Visual Perception /
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