no code implementations • 28 Nov 2023 • Haocheng Yuan, Jing Xu, Hao Pan, Adrien Bousseau, Niloy J. Mitra, Changjian Li
CAD programs are a popular way to compactly encode shapes as a sequence of operations that are easy to parametrically modify.
no code implementations • 28 Nov 2023 • Jiawei Wang, Changjian Li
Sketch semantic segmentation is a well-explored and pivotal problem in computer vision involving the assignment of pre-defined part labels to individual strokes.
1 code implementation • 13 Oct 2023 • Guangshun Wei, Hao Pan, Shaojie Zhuang, Yuanfeng Zhou, Changjian Li
To solve the non-uniformity of input points, on top of the cross field guided upsampling, we further introduce an iterative strategy that refines the point distribution by moving sparse points onto the desired continuous 3D surface in each iteration.
no code implementations • 26 Mar 2023 • Zhentao Liu, Yu Fang, Changjian Li, Han Wu, YuAn Liu, Zhiming Cui, Dinggang Shen
This paper proposes a novel attenuation field encoder-decoder framework by first encoding the volumetric feature from multi-view X-ray projections, then decoding it into the desired attenuation field.
no code implementations • 30 Nov 2022 • Yu Fang, Lanzhuju Mei, Changjian Li, YuAn Liu, Wenping Wang, Zhiming Cui, Dinggang Shen
Cone beam computed tomography (CBCT) has been widely used in clinical practice, especially in dental clinics, while the radiation dose of X-rays when capturing has been a long concern in CBCT imaging.
no code implementations • 25 Nov 2022 • Yuezhi Yang, Zhiming Cui, Changjian Li, Wenping Wang
In this paper, we propose a neural network, called ToothInpaintor, that takes as input a partial 3D dental model and a 2D panoramic image and reconstructs the full tooth model with high-quality root(s).
2 code implementations • CVPR 2021 • Cheng Lin, Changjian Li, YuAn Liu, Nenglun Chen, Yi-King Choi, Wenping Wang
We introduce Point2Skeleton, an unsupervised method to learn skeletal representations from point clouds.
1 code implementation • 15 Nov 2020 • Zihan Ding, Pablo Hernandez-Leal, Gavin Weiguang Ding, Changjian Li, Ruitong Huang
As a second contribution our study reveals limitations of explaining black-box policies via imitation learning with tree-based explainable models, due to its inherent instability.
1 code implementation • 22 Oct 2020 • Cheng Lin, Lingjie Liu, Changjian Li, Leif Kobbelt, Bin Wang, Shiqing Xin, Wenping Wang
Segmenting arbitrary 3D objects into constituent parts that are structurally meaningful is a fundamental problem encountered in a wide range of computer graphics applications.
no code implementations • 3 Jun 2020 • Zhi Shiuh Lim, Changjian Li, Zhen Huang, Xiao Chi, Jun Zhou, Shengwei Zeng, Ganesh Ji Omar, Yuan Ping Feng, Andrivo Rusydi, Stephen John Pennycook, Thirumalai Venkatesan, Ariando Ariando
Here, the emergence, tuning and interpretation of hump-shape Hall Effect from a CaMnO3/CaIrO3/CaMnO3 trilayer structure are studied in detail.
Mesoscale and Nanoscale Physics
1 code implementation • 27 Jan 2020 • Changjian Li
A lifelong reinforcement learning system is a learning system that has the ability to learn through trail-and-error interaction with the environment over its lifetime.
no code implementations • 24 May 2019 • Changjian Li, Krzysztof Czarnecki
The standard reinforcement learning (RL) formulation considers the expectation of the (discounted) cumulative reward.
no code implementations • ICCV 2019 • Cheng Lin, Changjian Li, Wenping Wang
We present a novel approach to align partial 3D reconstructions which may not have substantial overlap.
1 code implementation • 21 Nov 2018 • Changjian Li, Krzysztof Czarnecki
Autonomous driving is a challenging domain that entails multiple aspects: a vehicle should be able to drive to its destination as fast as possible while avoiding collision, obeying traffic rules and ensuring the comfort of passengers.