no code implementations • ECCV 2020 • Kunyuan Du, Ya zhang, Haibing Guan, Qi Tian, Shenggan Cheng, James Lin
Compared with low-bit models trained directly, the proposed framework brings 0. 5% to 3. 4% accuracy gains to three different quantization schemes.
1 code implementation • 2 Mar 2022 • Shenggan Cheng, Xuanlei Zhao, Guangyang Lu, Jiarui Fang, Zhongming Yu, Tian Zheng, Ruidong Wu, Xiwen Zhang, Jian Peng, Yang You
In this work, we present FastFold, an efficient implementation of AlphaFold for both training and inference.
no code implementations • 27 Aug 2018 • Zixuan Huang, Junming Fan, Shenggan Cheng, Shuai Yi, Xiaogang Wang, Hongsheng Li
Dense depth cues are important and have wide applications in various computer vision tasks.
Ranked #9 on Depth Completion on KITTI Depth Completion