Search Results for author: Zhibin Li

Found 20 papers, 4 papers with code

Self-attention on Multi-Shifted Windows for Scene Segmentation

1 code implementation10 Jul 2022 Litao Yu, Zhibin Li, Jian Zhang, Qiang Wu

Scene segmentation in images is a fundamental yet challenging problem in visual content understanding, which is to learn a model to assign every image pixel to a categorical label.

Scene Segmentation

Exploring Linear Feature Disentanglement For Neural Networks

no code implementations22 Mar 2022 Tiantian He, Zhibin Li, Yongshun Gong, Yazhou Yao, Xiushan Nie, Yilong Yin

Non-linear activation functions, e. g., Sigmoid, ReLU, and Tanh, have achieved great success in neural networks (NNs).


A cross-modal fusion network based on self-attention and residual structure for multimodal emotion recognition

1 code implementation3 Nov 2021 Ziwang Fu, Feng Liu, HanYang Wang, Jiayin Qi, Xiangling Fu, Aimin Zhou, Zhibin Li

Firstly, we perform representation learning for audio and video modalities to obtain the semantic features of the two modalities by efficient ResNeXt and 1D CNN, respectively.

Multimodal Emotion Recognition Representation Learning

EvoGAN: An Evolutionary Computation Assisted GAN

1 code implementation22 Oct 2021 Feng Liu, HanYang Wang, Jiahao Zhang, Ziwang Fu, Aimin Zhou, Jiayin Qi, Zhibin Li

Quantitative and Qualitative results are presented on several compound expressions, and the experimental results demonstrate the feasibility and the potential of EvoGAN.

Image Generation

Learning Perceptual Locomotion on Uneven Terrains using Sparse Visual Observations

no code implementations28 Sep 2021 Fernando Acero, Kai Yuan, Zhibin Li

To proactively navigate and traverse various terrains, active use of visual perception becomes indispensable.


Trajectory optimization for contact-rich motions using implicit differential dynamic programming

no code implementations20 Jan 2021 Iordanis Chatzinikolaidis, Zhibin Li

This paper presents a novel approach using sensitivity analysis for generalizing Differential Dynamic Programming (DDP) to systems characterized by implicit dynamics, such as those modelled via inverse dynamics and variational or implicit integrators.

Robotics Systems and Control Systems and Control

Meta-Reinforcement Learning for Adaptive Motor Control in Changing Robot Dynamics and Environments

no code implementations19 Jan 2021 Timothée Anne, Jack Wilkinson, Zhibin Li

This work developed a meta-learning approach that adapts the control policy on the fly to different changing conditions for robust locomotion.

Friction Meta-Learning +3

Multi-expert learning of adaptive legged locomotion

no code implementations10 Dec 2020 Chuanyu Yang, Kai Yuan, Qiuguo Zhu, Wanming Yu, Zhibin Li

Achieving versatile robot locomotion requires motor skills which can adapt to previously unseen situations.

Field-wise Learning for Multi-field Categorical Data

1 code implementation NeurIPS 2020 Zhibin Li, Jian Zhang, Yongshun Gong, Yazhou Yao, Qiang Wu

We present a model that utilizes linear models with variance and low-rank constraints, to help it generalize better and reduce the number of parameters.

Distribution-aware Margin Calibration for Medical Image Segmentation

no code implementations3 Nov 2020 Zhibin Li, Litao Yu, Jian Zhang

In this paper, we present a novel data-distribution-aware margin calibration method for a better generalization of the mIoU over the whole data-distribution, underpinned by a rigid lower bound.

Image Segmentation Medical Image Segmentation +1

Towards Better Graph Representation: Two-Branch Collaborative Graph Neural Networks for Multimodal Marketing Intention Detection

no code implementations13 May 2020 Lu Zhang, Jian Zhang, Zhibin Li, Jingsong Xu

Inspired by the fact that spreading and collecting information through the Internet becomes the norm, more and more people choose to post for-profit contents (images and texts) in social networks.

Graph Classification Marketing

Robust High-Transparency Haptic Exploration for Dexterous Telemanipulation

no code implementations3 Mar 2020 Keyhan Kouhkiloui Babarahmati, Carlo Tiseo, Quentin Rouxel, Zhibin Li, Michael Mistry

Robotic teleoperation will allow us to perform complex manipulation tasks in dangerous or remote environments, such as needed for planetary exploration or nuclear decommissioning.


Learning Pregrasp Manipulation of Objects from Ungraspable Poses

no code implementations15 Feb 2020 Zhaole Sun, Kai Yuan, Wenbin Hu, Chuanyu Yang, Zhibin Li

In robotic grasping, objects are often occluded in ungraspable configurations such that no pregrasp pose can be found, eg large flat boxes on the table that can only be grasped from the side.


Reaching, Grasping and Re-grasping: Learning Fine Coordinated Motor Skills

no code implementations11 Feb 2020 Wenbin Hu, Chuanyu Yang, Kai Yuan, Zhibin Li

The performance of learned policy is evaluated on three different tasks: grasping a static target, grasping a dynamic target, and re-grasping.


Learning Whole-body Motor Skills for Humanoids

no code implementations7 Feb 2020 Chuanyu Yang, Kai Yuan, Wolfgang Merkt, Taku Komura, Sethu Vijayakumar, Zhibin Li

This paper presents a hierarchical framework for Deep Reinforcement Learning that acquires motor skills for a variety of push recovery and balancing behaviors, i. e., ankle, hip, foot tilting, and stepping strategies.

Force-guided High-precision Grasping Control of Fragile and Deformable Objects using sEMG-based Force Prediction

no code implementations5 Feb 2020 Ruoshi Wen, Kai Yuan, Qiang Wang, Shuai Heng, Zhibin Li

Regulating contact forces with high precision is crucial for grasping and manipulating fragile or deformable objects.


Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development

no code implementations7 Dec 2019 Yongshun Gong, Zhibin Li, Jian Zhang, Wei Liu, Jin-Feng Yi

In this paper, this specific problem is termed as potential passenger flow (PPF) prediction, which is a novel and important study connected with urban computing and intelligent transportation systems.

MULTI-VIEW LEARNING Recommendation Systems

Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points

no code implementations2 Jul 2019 Zhibin Li, Jian Zhang, Qiang Wu, Yongshun Gong, Jin-Feng Yi, Christina Kirsch

In this paper, we formulate our prediction task as a multiple kernel learning problem with missing kernels.

Recurrent Deterministic Policy Gradient Method for Bipedal Locomotion on Rough Terrain Challenge

no code implementations8 Oct 2017 Doo Re Song, Chuanyu Yang, Christopher McGreavy, Zhibin Li

This paper presents a deep learning framework that is capable of solving partially observable locomotion tasks based on our novel interpretation of Recurrent Deterministic Policy Gradient (RDPG).

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