Cambricon-R: A Fully Fused Accelerator for Real-Time Learning of Neural Scene Representation
Xinkai Song, Yuanbo Wen, Xing Hu, Tianbo Liu, H. Zhou, Husheng Han, Tian Zhi, Zidong Du, Wei Li, Rui Zhang, Chen Zhang, Lin Gao, Qi Guo, Tianshi Chen
Abstract
Neural scene representation (NSR) initiates a new methodology of encoding a 3D scene with neural networks by learning from dozens of photos taken from different camera positions. NSR not only achieves significant improvement in the quality of novel view synthesis and 3D reconstruction but also reduces the camera cost from the expensive laser cameras to the cheap color cameras on the shelf. However, performing 3D scene encoding using NSR is far from real-time due to the extremely low hardware utilization (only utilization of hardware peak performance), which greatly limits its applications in real-time AR/VR interactions