Search Results for author: Tianhao Wu

Found 12 papers, 6 papers with code

GraspARL: Dynamic Grasping via Adversarial Reinforcement Learning

no code implementations4 Mar 2022 Tianhao Wu, Fangwei Zhong, Yiran Geng, Hongchen Wang, Yongjian Zhu, Yizhou Wang, Hao Dong

we formulate the dynamic grasping problem as a 'move-and-grasp' game, where the robot is to pick up the object on the mover and the adversarial mover is to find a path to escape it.


$ \text{T}^3 $OMVP: A Transformer-based Time and Team Reinforcement Learning Scheme for Observation-constrained Multi-Vehicle Pursuit in Urban Area

1 code implementation1 Mar 2022 Zheng Yuan, Tianhao Wu, Qinwen Wang, Yiying Yang, Lei LI, Lin Zhang

Although there are some achievements in the field of MVP in the open space environment, the urban area brings complicated road structures and restricted moving spaces as challenges to the resolution of MVP games.

Decision Making

Nearly Optimal Policy Optimization with Stable at Any Time Guarantee

no code implementations21 Dec 2021 Tianhao Wu, Yunchang Yang, Han Zhong, LiWei Wang, Simon S. Du, Jiantao Jiao

Policy optimization methods are one of the most widely used classes of Reinforcement Learning (RL) algorithms.

A Credibility-aware Swarm-Federated Deep Learning Framework in Internet of Vehicles

1 code implementation9 Aug 2021 Zhe Wang, Xinhang Li, Tianhao Wu, Chen Xu, Lin Zhang

This paper proposes a Swarm-Federated Deep Learning framework in the IoV system (IoV-SFDL) that integrates SL into the FDL framework.


VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects

no code implementations ICLR 2022 Ruihai Wu, Yan Zhao, Kaichun Mo, Zizheng Guo, Yian Wang, Tianhao Wu, Qingnan Fan, Xuelin Chen, Leonidas Guibas, Hao Dong

In this paper, we propose object-centric actionable visual priors as a novel perception-interaction handshaking point that the perception system outputs more actionable guidance than kinematic structure estimation, by predicting dense geometry-aware, interaction-aware, and task-aware visual action affordance and trajectory proposals.

A Multi-intersection Vehicular Cooperative Control based on End-Edge-Cloud Computing

no code implementations1 Dec 2020 Mingzhi Jiang, Tianhao Wu, Zhe Wang, Yi Gong, Lin Zhang, Ren Ping Liu

In particular, we propose a Multi-intersection Vehicular Cooperative Control (MiVeCC) to enable cooperation among vehicles in a large area with multiple unsignalized intersections.

Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot

1 code implementation NeurIPS 2020 Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Li-Wei Wang, Jason D. Lee

In this paper, we conduct sanity checks for the above beliefs on several recent unstructured pruning methods and surprisingly find that: (1) A set of methods which aims to find good subnetworks of the randomly-initialized network (which we call "initial tickets"), hardly exploits any information from the training data; (2) For the pruned networks obtained by these methods, randomly changing the preserved weights in each layer, while keeping the total number of preserved weights unchanged per layer, does not affect the final performance.

Network Pruning

Light Field Image Super-Resolution Using Deformable Convolution

1 code implementation7 Jul 2020 Yingqian Wang, Jungang Yang, Longguang Wang, Xinyi Ying, Tianhao Wu, Wei An, Yulan Guo

In this paper, we propose a deformable convolution network (i. e., LF-DFnet) to handle the disparity problem for LF image SR.

Image Super-Resolution

DeOccNet: Learning to See Through Foreground Occlusions in Light Fields

1 code implementation10 Dec 2019 Yingqian Wang, Tianhao Wu, Jungang Yang, Longguang Wang, Wei An, Yulan Guo

In this paper, we handle the LF de-occlusion (LF-DeOcc) problem using a deep encoder-decoder network (namely, DeOccNet).

Cannot find the paper you are looking for? You can Submit a new open access paper.