1 code implementation • 3 Feb 2023 • ZiHao Wang, Shaofei Cai, Anji Liu, Xiaojian Ma, Yitao Liang
In this paper, we study the problem of planning in Minecraft, a popular, democratized yet challenging open-ended environment for developing multi-task embodied agents.
2 code implementations • 21 Jan 2023 • Shaofei Cai, ZiHao Wang, Xiaojian Ma, Anji Liu, Yitao Liang
We study the problem of learning goal-conditioned policies in Minecraft, a popular, widely accessible yet challenging open-ended environment for developing human-level multi-task agents.
1 code implementation • 28 Nov 2022 • Jiangyong Huang, William Yicheng Zhu, Baoxiong Jia, Zan Wang, Xiaojian Ma, Qing Li, Siyuan Huang
Current computer vision models, unlike the human visual system, cannot yet achieve general-purpose visual understanding.
1 code implementation • 14 Oct 2022 • Xiaojian Ma, Silong Yong, Zilong Zheng, Qing Li, Yitao Liang, Song-Chun Zhu, Siyuan Huang
We propose a new task to benchmark scene understanding of embodied agents: Situated Question Answering in 3D Scenes (SQA3D).
Ranked #1 on
Question Answering
on SQA3D
(using extra training data)
1 code implementation • 30 Jun 2022 • Liangzhe Han, Xiaojian Ma, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv, Hui Xiong
Traffic demand forecasting by deep neural networks has attracted widespread interest in both academia and industry society.
1 code implementation • 13 Jun 2022 • Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, Ying Nian Wu
Latent space Energy-Based Models (EBMs), also known as energy-based priors, have drawn growing interests in generative modeling.
1 code implementation • CVPR 2022 • Huaizu Jiang, Xiaojian Ma, Weili Nie, Zhiding Yu, Yuke Zhu, Anima Anandkumar
A significant gap remains between today's visual pattern recognition models and human-level visual cognition especially when it comes to few-shot learning and compositional reasoning of novel concepts.
Ranked #1 on
Few-Shot Image Classification
on Bongard-HOI
1 code implementation • ICLR 2022 • Xiaojian Ma, Weili Nie, Zhiding Yu, Huaizu Jiang, Chaowei Xiao, Yuke Zhu, Song-Chun Zhu, Anima Anandkumar
This task remains challenging for current deep learning algorithms since it requires addressing three key technical problems jointly: 1) identifying object entities and their properties, 2) inferring semantic relations between pairs of entities, and 3) generalizing to novel object-relation combinations, i. e., systematic generalization.
Ranked #1 on
Zero-Shot Human-Object Interaction Detection
on HICO
1 code implementation • NeurIPS 2021 • Peiyu Yu, Sirui Xie, Xiaojian Ma, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
Foreground extraction can be viewed as a special case of generic image segmentation that focuses on identifying and disentangling objects from the background.
1 code implementation • 10 Jun 2021 • Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei LI
In particular, we propose an Expectation-Maximization(EM)-style algorithm: an E-step that samples the options of expert conditioned on the current learned policy, and an M-step that updates the low- and high-level policies of agent simultaneously to minimize the newly proposed option-occupancy measurement between the expert and the agent.
no code implementations • 22 Feb 2021 • Sirui Xie, Xiaojian Ma, Peiyu Yu, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
Leveraging these concepts, they could understand the internal structure of this task, without seeing all of the problem instances.
1 code implementation • 11 Mar 2020 • Shuang Li, Jiaxi Jiang, Philipp Ruppel, Hongzhuo Liang, Xiaojian Ma, Norman Hendrich, Fuchun Sun, Jianwei Zhang
In this paper, we present a multimodal mobile teleoperation system that consists of a novel vision-based hand pose regression network (Transteleop) and an IMU-based arm tracking method.
1 code implementation • 29 Feb 2020 • Hongzhuo Liang, Chuangchuang Zhou, Shuang Li, Xiaojian Ma, Norman Hendrich, Timo Gerkmann, Fuchun Sun, Marcus Stoffel, Jianwei Zhang
Both network training results and robot experiments demonstrate that MP-Net is robust against noise and changes to the task and environment.
no code implementations • 25 Nov 2019 • Mark Edmonds, Xiaojian Ma, Siyuan Qi, Yixin Zhu, Hongjing Lu, Song-Chun Zhu
Given these general theories, the goal is to train an agent by interactively exploring the problem space to (i) discover, form, and transfer useful abstract and structural knowledge, and (ii) induce useful knowledge from the instance-level attributes observed in the environment.
no code implementations • 16 Nov 2019 • Mingxuan Jing, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Chao Yang, Bin Fang, Huaping Liu
In this paper, we study Reinforcement Learning from Demonstrations (RLfD) that improves the exploration efficiency of Reinforcement Learning (RL) by providing expert demonstrations.
no code implementations • NeurIPS 2019 • Chao Yang, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Huaping Liu, Junzhou Huang, Chuang Gan
This paper studies Learning from Observations (LfO) for imitation learning with access to state-only demonstrations.
1 code implementation • 2 Mar 2019 • Hongzhuo Liang, Shuang Li, Xiaojian Ma, Norman Hendrich, Timo Gerkmann, Jianwei Zhang
PouringNet is trained on our collected real-world pouring dataset with multimodal sensing data, which contains more than 3000 recordings of audio, force feedback, video and trajectory data of the human hand that performs the pouring task.
Robotics Sound Audio and Speech Processing
4 code implementations • 17 Sep 2018 • Hongzhuo Liang, Xiaojian Ma, Shuang Li, Michael Görner, Song Tang, Bin Fang, Fuchun Sun, Jianwei Zhang
In this paper, we propose an end-to-end grasp evaluation model to address the challenging problem of localizing robot grasp configurations directly from the point cloud.
Robotics
4 code implementations • 17 Sep 2018 • Shuang Li, Xiaojian Ma, Hongzhuo Liang, Michael Görner, Philipp Ruppel, Bing Fang, Fuchun Sun, Jianwei Zhang
In this paper, we present TeachNet, a novel neural network architecture for intuitive and markerless vision-based teleoperation of dexterous robotic hands.
Robotics
no code implementations • 18 May 2018 • Mingxuan Jing, Xiaojian Ma, Fuchun Sun, Huaping Liu
Learning and inference movement is a very challenging problem due to its high dimensionality and dependency to varied environments or tasks.
no code implementations • 12 May 2018 • Mingxuan Jing, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Huaping Liu
The goal of task transfer in reinforcement learning is migrating the action policy of an agent to the target task from the source task.