no code implementations • 2 Nov 2023 • Hang Chen, Keqing Du, Chenguang Li, Xinyu Yang
The fusion of causal models with deep learning introducing increasingly intricate data sets, such as the causal associations within images or between textual components, has surfaced as a focal research area.
no code implementations • 14 Sep 2022 • Hang Chen, Keqing Du, Xinyu Yang, Chenguang Li
Understanding causality helps to structure interventions to achieve specific goals and enables predictions under interventions.
no code implementations • 21 Jun 2022 • Chenguang Li, Jia Shi, Ya Wang, Guangliang Cheng
Inspired by previous methods, we first analyze the geometry heuristic between the 3D lane and its 2D representation on the ground and propose to impose explicit supervision based on the structure prior, which makes it achievable to build inter-lane and intra-lane relationships to facilitate the reconstruction of 3D lanes from local to global.
no code implementations • 21 Jun 2022 • Chenguang Li, Boheng Zhang, Jia Shi, Guangliang Cheng
We focus on bridging domain discrepancy in lane detection among different scenarios to greatly reduce extra annotation and re-training costs for autonomous driving.
no code implementations • CVPR 2022 • Chenguang Li, Jia Shi, Ya Wang, Guangliang Cheng
Inspired by previous methods, we first analyze the geometry heuristic between the 3D lane and its 2D representation on the ground and propose to impose explicit supervision based on the structure prior, which makes it achievable to build inter-lane and intra-lane relationships to facilitate the reconstruction of 3D lanes from local to global.
Ranked #7 on 3D Lane Detection on Apollo Synthetic 3D Lane
no code implementations • NeurIPS Workshop SVRHM 2021 • Chenguang Li, Arturo Deza
What motivates the brain to allocate tasks to different regions and what distinguishes multiple-demand brain regions and the tasks they perform from ones in highly specialized areas?
no code implementations • ACL 2019 • Jiangjie Chen, Ao Wang, Haiyun Jiang, Suo Feng, Chenguang Li, Yanghua Xiao
A type description is a succinct noun compound which helps human and machines to quickly grasp the informative and distinctive information of an entity.
no code implementations • 28 Aug 2018 • Shi Yin, Yi Zhou, Chenguang Li, Shangfei Wang, Jianmin Ji, Xiaoping Chen, Ruili Wang
We propose KDSL, a new word sense disambiguation (WSD) framework that utilizes knowledge to automatically generate sense-labeled data for supervised learning.