35 papers
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware
Shichang Zhang, Atefeh Sohrabizadeh, Cheng Wan +7
Graph neural networks (GNNs) are emerging for machine learning research on graph-structured data. GNNs achieve state-of-the-art performance on many tasks, but they face scalability…
Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstruction
Sixu Li, Chaojian Li, Wenbo Zhu +6
Neural Radiance Field (NeRF) based 3D reconstruction is highly desirable for immersive Augmented and Virtual Reality (AR/VR) applications, but achieving instant (i.e., < 5 seconds)…
ERSAM: Neural Architecture Search For Energy-Efficient and Real-Time Social Ambiance Measurement
Chaojian Li, Wenwan Chen, Jiayi Yuan +2
Social ambiance describes the context in which social interactions happen, and can be measured using speech audio by counting the number of concurrent speakers. This measurement ha…
INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors
Chaojian Li, Bichen Wu, Albert Pumarola +3
We present a method that accelerates reconstruction of 3D scenes and objects, aiming to enable instant reconstruction on edge devices such as mobile phones and AR/VR headsets. Whil…
RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering
Chaojian Li, Sixu Li, Yang Zhao +2
Neural Radiance Field (NeRF) based rendering has attracted growing attention thanks to its state-of-the-art (SOTA) rendering quality and wide applications in Augmented and Virtual…
i-FlatCam: A 253 FPS, 91.49 J/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR
Yang Zhao, Ziyun Li, Yonggan Fu +9
We present a first-of-its-kind ultra-compact intelligent camera system, dubbed i-FlatCam, including a lensless camera with a computational (Comp.) chip. It highlights (1) a predict…