D$^2$-GCN: Data-Dependent GCNs for Boosting Both Efficiency and Scalability

no code implementations • 29 Sep 2021 • Chaojian Li, Xu Ouyang, Yang Zhao, Haoran You, Yonggan Fu, Yuchen Gu, Haonan Liu, Siyuan Miao, Yingyan Lin

Graph Convolutional Networks (GCNs) have gained an increasing attention thanks to their state-of-the-art (SOTA) performance in graph-based learning tasks.

DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference

no code implementations • 16 Jul 2021 • Chaojian Li, Wuyang Chen, Yuchen Gu, Tianlong Chen, Yonggan Fu, Zhangyang Wang, Yingyan Lin

Semantic segmentation for scene understanding is nowadays widely demanded, raising significant challenges for the algorithm efficiency, especially its applications on resource-limited platforms.

Scene Understanding Segmentation +1