1 code implementation • 13 Mar 2024 • Qinglong Meng, Chongkun Xia, Xueqian Wang
To implement PaddingFlow, only the dimension of normalizing flows needs to be modified.
Ranked #1 on Density Estimation on MNIST (MMD-L2 metric)
1 code implementation • 18 Jan 2024 • Qinglong Meng, Chongkun Xia, Xueqian Wang, Songping Mai, Bin Liang
The results show that PPNet can find a near-optimal solution in 15. 3ms, which is much shorter than the state-of-the-art path planners.
no code implementations • 21 Feb 2023 • Yuhong Deng, Chongkun Xia, Xueqian Wang, Lipeng Chen
Some research has been attempting to design a general framework to obtain more advanced manipulation capabilities for deformable rearranging tasks, with lots of progress achieved in simulation.
no code implementations • 21 Feb 2023 • Yuhong Deng, Chongkun Xia, Xueqian Wang, Lipeng Chen
Rearranging deformable objects is a long-standing challenge in robotic manipulation for the high dimensionality of configuration space and the complex dynamics of deformable objects.
1 code implementation • 8 Jan 2023 • Kai Mo, Chongkun Xia, Xueqian Wang, Yuhong Deng, Xuehai Gao, Bin Liang
Foldformer can complete multi-step cloth manipulation tasks even when configurations of the cloth (e. g., size and pose) vary from configurations in the general demonstrations.
no code implementations • 30 Nov 2022 • Shoujie Li, Haixin Yu, Wenbo Ding, Houde Liu, Linqi Ye, Chongkun Xia, Xueqian Wang, Xiao-Ping Zhang
Here, a visual-tactile fusion framework for transparent object grasping under complex backgrounds and variant light conditions is proposed, including the grasping position detection, tactile calibration, and visual-tactile fusion based classification.
1 code implementation • 25 Aug 2022 • Mingqi Shao, Chongkun Xia, Dongxu Duan, Xueqian Wang
We build a polarization dataset for multi-view transparent shapes reconstruction to verify our method.
1 code implementation • ICCV 2023 • Mingqi Shao, Chongkun Xia, Zhendong Yang, Junnan Huang, Xueqian Wang
To train and test our method, we construct a dataset for transparent shape from polarization with paired polarization images and ground-truth normal maps.