Search Results for author: Lijun Wang

Found 21 papers, 6 papers with code

CLIFFNet for Monocular Depth Estimation with Hierarchical Embedding Loss

no code implementations ECCV 2020 Lijun Wang, Jianming Zhang, Yifan Wang, Huchuan Lu, Xiang Ruan

This paper proposes a hierarchical loss for monocular depth estimation, which measures the differences between the prediction and ground truth in hierarchical embedding spaces of depth maps.

Monocular Depth Estimation

Blind estimation of room acoustic parameters from speech signals based on extended model of room impulse response

no code implementations26 Dec 2022 Lijun Wang, Suradej Duangpummet, Masashi Unoki

The root-mean-square errors between the estimated and ground-truth results were used to comparatively evaluate the proposed method with the previous method.

Multi-Source Uncertainty Mining for Deep Unsupervised Saliency Detection

no code implementations CVPR 2022 Yifan Wang, Wenbo Zhang, Lijun Wang, Ting Liu, Huchuan Lu

We design an Uncertainty Mining Network (UMNet) which consists of multiple Merge-and-Split (MS) modules to recursively analyze the commonality and difference among multiple noisy labels and infer pixel-wise uncertainty map for each label.

object-detection Object Detection +3

Comparison between Time Shifting Deviation and Cross-correlation Methods

no code implementations15 Nov 2021 Zhongwang Pang, Guan Wang, Bo wang, Lijun Wang

It stands in clear contrast to the result of cross-correlation method, whose localization error is 70 m and the standard deviation is 208. 4 m. Compared with cross-correlation method, TSDEV has the same resistance to white noise, but has fewer boundary conditions and better suppression on linear drift or common noise, which leads to more precise TDE results.

Towards Toxic and Narcotic Medication Detection with Rotated Object Detector

1 code implementation19 Oct 2021 Jiao Peng, Feifan Wang, Zhongqiang Fu, Yiying Hu, Zichen Chen, Xinghan Zhou, Lijun Wang

Recent years have witnessed the advancement of deep learning vision technologies and applications in the medical industry.


Video Annotation for Visual Tracking via Selection and Refinement

1 code implementation ICCV 2021 Kenan Dai, Jie Zhao, Lijun Wang, Dong Wang, Jianhua Li, Huchuan Lu, Xuesheng Qian, Xiaoyun Yang

Deep learning based visual trackers entail offline pre-training on large volumes of video datasets with accurate bounding box annotations that are labor-expensive to achieve.

Visual Tracking

A Single Frame and Multi-Frame Joint Network for 360-degree Panorama Video Super-Resolution

2 code implementations24 Aug 2020 Hongying Liu, Zhubo Ruan, Chaowei Fang, Peng Zhao, Fanhua Shang, Yuanyuan Liu, Lijun Wang

Spherical videos, also known as \ang{360} (panorama) videos, can be viewed with various virtual reality devices such as computers and head-mounted displays.

Video Super-Resolution

Appearance-free Tripartite Matching for Multiple Object Tracking

1 code implementation9 Aug 2020 Lijun Wang, Yanting Zhu, Jue Shi, Xiaodan Fan

We focus on the general MOT problem regardless of the appearance and propose an appearance-free tripartite matching to avoid the irregular velocity problem of the bipartite matching.

Multiple Object Tracking

When Relation Networks meet GANs: Relation GANs with Triplet Loss

1 code implementation24 Feb 2020 Runmin Wu, Kunyao Zhang, Lijun Wang, Yue Wang, Pingping Zhang, Huchuan Lu, Yizhou Yu

Though recent research has achieved remarkable progress in generating realistic images with generative adversarial networks (GANs), the lack of training stability is still a lingering concern of most GANs, especially on high-resolution inputs and complex datasets.

Conditional Image Generation Translation

DeepLens: Shallow Depth Of Field From A Single Image

no code implementations18 Oct 2018 Lijun Wang, Xiaohui Shen, Jianming Zhang, Oliver Wang, Zhe Lin, Chih-Yao Hsieh, Sarah Kong, Huchuan Lu

To achieve this, we propose a novel neural network model comprised of a depth prediction module, a lens blur module, and a guided upsampling module.

Depth Estimation Depth Prediction

Learning regression and verification networks for long-term visual tracking

3 code implementations12 Sep 2018 Yunhua Zhang, Dong Wang, Lijun Wang, Jinqing Qi, Huchuan Lu

Compared with short-term tracking, the long-term tracking task requires determining the tracked object is present or absent, and then estimating the accurate bounding box if present or conducting image-wide re-detection if absent.

General Classification Region Proposal +2

Structured Siamese Network for Real-Time Visual Tracking

no code implementations ECCV 2018 Yunhua Zhang, Lijun Wang, Jinqing Qi, Dong Wang, Mengyang Feng, Huchuan Lu

In this paper, we circumvent this issue by proposing a local structure learning method, which simultaneously considers the local patterns of the target and their structural relationships for more accurate target tracking.

Real-Time Visual Tracking

Visual Tracking via Shallow and Deep Collaborative Model

no code implementations27 Jul 2016 Bohan Zhuang, Lijun Wang, Huchuan Lu

In the discriminative model, we exploit the advances of deep learning architectures to learn generic features which are robust to both background clutters and foreground appearance variations.

Incremental Learning Visual Tracking

End-to-End Image Super-Resolution via Deep and Shallow Convolutional Networks

no code implementations26 Jul 2016 Yifan Wang, Lijun Wang, Hongyu Wang, Peihua Li

In this paper, we seek an alternative and propose a new image SR method, which jointly learns the feature extraction, upsampling and HR reconstruction modules, yielding a completely end-to-end trainable deep CNN.

Image Super-Resolution

STCT: Sequentially Training Convolutional Networks for Visual Tracking

no code implementations CVPR 2016 Lijun Wang, Wanli Ouyang, Xiaogang Wang, Huchuan Lu

To further improve the robustness of each base learner, we propose to train the convolutional layers with random binary masks, which serves as a regularization to enforce each base learner to focus on different input features.

Visual Tracking

Visual Tracking With Fully Convolutional Networks

no code implementations ICCV 2015 Lijun Wang, Wanli Ouyang, Xiaogang Wang, Huchuan Lu

Instead of treating convolutional neural network (CNN) as a black-box feature extractor, we conduct in-depth study on the properties of CNN features offline pre-trained on massive image data and classification task on ImageNet.

Object Tracking Visual Tracking

Deep Networks for Saliency Detection via Local Estimation and Global Search

no code implementations CVPR 2015 Lijun Wang, Huchuan Lu, Xiang Ruan, Ming-Hsuan Yang

In the global search stage, the local saliency map together with global contrast and geometric information are used as global features to describe a set of object candidate regions.

Saliency Detection

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