181 citations · 209 across the 11 of their papers we have counts for
4 papers · 1 filter
MMBench: Benchmarking End-to-End Multi-modal DNNs and Understanding Their Hardware-Software Implications
Cheng Xu, Xiaofeng Hou, Jiacheng Liu +9
The explosive growth of various types of big data and advances in AI technologies have catalyzed a new type of workloads called multi-modal DNNs. Multi-modal DNNs are capable of in…
Omni-Dimensional Dynamic Convolution
Chao Li, Aojun Zhou, Anbang Yao
Learning a single static convolutional kernel in each convolutional layer is the common training paradigm of modern Convolutional Neural Networks (CNNs). Instead, recent research i…
DRKF: Distilled Rotated Kernel Fusion for Efficient Rotation Invariant Descriptors in Local Feature Matching
Ranran Huang, Jiancheng Cai, Chao Li +3
The performance of local feature descriptors degrades in the presence of large rotation variations. To address this issue, we present an efficient approach to learning rotation inv…
On The Design of a Light-weight FPGA Programming Framework for Graph Applications
Jing Wang, Jinyang Guo, Chao Li
FPGA accelerators designed for graph processing are gaining popularity. Domain Specific Language (DSL) frameworks for graph processing can reduce the programming complexity and dev…