Search Results for author: Xiaoqin Zhang

Found 11 papers, 0 papers with code

DcnnGrasp: Towards Accurate Grasp Pattern Recognition with Adaptive Regularizer Learning

no code implementations11 May 2022 Xiaoqin Zhang, Ziwei Huang, Jingjing Zheng, Shuo Wang, Xianta Jiang

The task of grasp pattern recognition aims to derive the applicable grasp types of an object according to the visual information.

Infrared and Visible Image Fusion via Interactive Compensatory Attention Adversarial Learning

no code implementations29 Mar 2022 Zhishe Wang, Wenyu Shao, Yanlin Chen, Jiawei Xu, Xiaoqin Zhang

The existing generative adversarial fusion methods generally concatenate source images and extract local features through convolution operation, without considering their global characteristics, which tends to produce an unbalanced result and is biased towards the infrared image or visible image.

Infrared And Visible Image Fusion

Semantics-Guided Contrastive Network for Zero-Shot Object detection

no code implementations4 Sep 2021 Caixia Yan, Xiaojun Chang, Minnan Luo, Huan Liu, Xiaoqin Zhang, Qinghua Zheng

To address these issues, we develop a novel Semantics-Guided Contrastive Network for ZSD, named ContrastZSD, a detection framework that first brings contrastive learning mechanism into the realm of zero-shot detection.

Contrastive Learning Zero-Shot Object Detection

Referring Segmentation in Images and Videos with Cross-Modal Self-Attention Network

no code implementations9 Feb 2021 Linwei Ye, Mrigank Rochan, Zhi Liu, Xiaoqin Zhang, Yang Wang

In this paper, we propose a cross-modal self-attention (CMSA) module to utilize fine details of individual words and the input image or video, which effectively captures the long-range dependencies between linguistic and visual features.

Ranked #4 on Referring Expression Segmentation on J-HMDB (Precision@0.9 metric)

Frame Referring Expression +3

Self-Weighted Robust LDA for Multiclass Classification with Edge Classes

no code implementations24 Sep 2020 Caixia Yan, Xiaojun Chang, Minnan Luo, Qinghua Zheng, Xiaoqin Zhang, Zhihui Li, Feiping Nie

In this regard, a novel self-weighted robust LDA with l21-norm based pairwise between-class distance criterion, called SWRLDA, is proposed for multi-class classification especially with edge classes.

Classification General Classification +1

Pretrain Soft Q-Learning with Imperfect Demonstrations

no code implementations9 May 2019 Xiaoqin Zhang, Yunfei Li, Huimin Ma, Xiong Luo

Pretraining reinforcement learning methods with demonstrations has been an important concept in the study of reinforcement learning since a large amount of computing power is spent on online simulations with existing reinforcement learning algorithms.

Q-Learning reinforcement-learning

Pretraining Deep Actor-Critic Reinforcement Learning Algorithms With Expert Demonstrations

no code implementations31 Jan 2018 Xiaoqin Zhang, Huimin Ma

We apply our method to two of the typical actor-critic reinforcement learning algorithms, DDPG and ACER, and demonstrate with experiments that our method not only outperforms the RL algorithms without pretraining process, but also is more simulation efficient.

reinforcement-learning

Constructive neural network learning

no code implementations30 Apr 2016 Shaobo Lin, Jinshan Zeng, Xiaoqin Zhang

In this paper, we aim at developing scalable neural network-type learning systems.

Local Subspace Collaborative Tracking

no code implementations ICCV 2015 Lin Ma, Xiaoqin Zhang, Weiming Hu, Junliang Xing, Jiwen Lu, Jie zhou

To address this, this paper presents a local subspace collaborative tracking method for robust visual tracking, where multiple linear and nonlinear subspaces are learned to better model the nonlinear relationship of object appearances.

Object Tracking Visual Tracking

Multiple Object Tracking: A Literature Review

no code implementations26 Sep 2014 Wenhan Luo, Junliang Xing, Anton Milan, Xiaoqin Zhang, Wei Liu, Tae-Kyun Kim

We inspect the recent advances in various aspects and propose some interesting directions for future research.

Multiple Object Tracking

Simultaneous Rectification and Alignment via Robust Recovery of Low-rank Tensors

no code implementations NeurIPS 2013 Xiaoqin Zhang, Di Wang, Zhengyuan Zhou, Yi Ma

In this context, the state-of-the-art algorithms RASL'' and "TILT'' can be viewed as two special cases of our work, and yet each only performs part of the function of our method."

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