no code implementations • 7 Mar 2024 • Leilei Jin, Jiajie Xu, Wenjie Fu, Hao Yan, Longxing Shi
With shrinking interconnect spacing in advanced technology nodes, existing timing predictions become less precise due to the challenging quantification of crosstalk-induced delay.
1 code implementation • 24 Aug 2023 • Dakshit Agrawal, Jiajie Xu, Siva Karthik Mustikovela, Ioannis Gkioulekas, Ashish Shrivastava, Yuning Chai
We propose a novel-view augmentation (NOVA) strategy to train NeRFs for photo-realistic 3D composition of dynamic objects in a static scene.
2 code implementations • 21 Mar 2022 • Li Chen, Chonghao Sima, Yang Li, Zehan Zheng, Jiajie Xu, Xiangwei Geng, Hongyang Li, Conghui He, Jianping Shi, Yu Qiao, Junchi Yan
Methods for 3D lane detection have been recently proposed to address the issue of inaccurate lane layouts in many autonomous driving scenarios (uphill/downhill, bump, etc.).
Ranked #5 on 3D Lane Detection on Apollo Synthetic 3D Lane
no code implementations • 20 Nov 2021 • Yunyi Li, Pengpeng Zhao, Guanfeng Liu, Yanchi Liu, Victor S. Sheng, Jiajie Xu, Xiaofang Zhou
In this paper, we propose an Edge-Enhanced Global Disentangled Graph Neural Network (EGD-GNN) model to capture the relation information between items for global item representation and local user intention learning.
no code implementations • 25 May 2021 • Zhongzhen Luo, Fengjia Zhang, Guoyi Fu, Jiajie Xu
Depth completion aims at inferring a dense depth image from sparse depth measurement since glossy, transparent or distant surface cannot be scanned properly by the sensor.
no code implementations • 8 Feb 2020 • Zafaryab Rasool, Rui Zhou, Lu Chen, Chengfei Liu, Jiajie Xu
Efficient query algorithms are proposed for these indices which significantly avoids irrelevant comparisons at the cost of space.
no code implementations • IEEE Transactions on Knowledge and Data Engineering 2019 • Jiajie Xu, Jing Zhao, Rui Zhou, Chengfei Liu
However, the standard attention mechanism uses fixed feature representations, and has a limited ability to represent distinct features of locations.
no code implementations • 29 May 2019 • Jian Liu, Pengpeng Zhao, Yanchi Liu, Victor S. Sheng, Fuzheng Zhuang, Jiajie Xu, Xiaofang Zhou, Hui Xiong
Then, we integrate the aesthetic features into a cross-domain network to transfer users' domain independent aesthetic preferences.
no code implementations • 18 Jun 2018 • Pengpeng Zhao, Haifeng Zhu, Yanchi Liu, Zhixu Li, Jiajie Xu, Victor S. Sheng
Furthermore, to reduce the number of parameters and improve efficiency, we further integrate coupled input and forget gates with our proposed model.