Learning Situation Hyper-Graphs for Video Question Answering
Aisha Urooj Khan, Hilde Kuehne, et al.
CVPR 2023
We present a scalable, commodity-based, parallel rendering system for interactive visualization of large polygonal and volumetric data models. Our system utilizes commodity PCs that have multiple CPUs and high-capacity I/O buses, a fast AGP bus, and a commodity interconnect. Rendering occurs in parallel using the Chromium framework with the resulting images displayed over the network on a remote display. A key component of our system is the Scalable Graphics Engine, a network-attached video framebuffer capable of gathering pixels from up to 16 sources and driving multiple displays. Our experimental results show that recent developments in commodity computers favor parallel architectures designed to use framebuffer readback and pixel transfer over commodity networks versus specialized hardware for acquiring and aggregating pixel data. © 2003 Elsevier Ltd. All rights reserved.
Aisha Urooj Khan, Hilde Kuehne, et al.
CVPR 2023
Zhixian Yan, Dipanjan Chakraborty, et al.
EDBT 2011
Orly Stettiner, Dan Chazan
ICPR 1994
Fearghal O'Donncha, Albert Akhriev, et al.
Big Data 2021