Search Results for author: Xiang Ruan

Found 9 papers, 1 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

Self-Supervised Representation Learning for RGB-D Salient Object Detection

no code implementations29 Jan 2021 Xiaoqi Zhao, Youwei Pang, Lihe Zhang, Huchuan Lu, Xiang Ruan

Existing CNNs-Based RGB-D Salient Object Detection (SOD) networks are all required to be pre-trained on the ImageNet to learn the hierarchy features which can help to provide a good initialization.

Representation Learning RGB-D Salient Object Detection +1

Detect Globally, Refine Locally: A Novel Approach to Saliency Detection

no code implementations CVPR 2018 Tiantian Wang, Lihe Zhang, Shuo Wang, Huchuan Lu, Gang Yang, Xiang Ruan, Ali Borji

Moreover, to effectively recover object boundaries, we propose a local Boundary Refinement Network (BRN) to adaptively learn the local contextual information for each spatial position.

RGB Salient Object Detection Saliency Detection +1

Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection

1 code implementation ICCV 2017 Pingping Zhang, Dong Wang, Huchuan Lu, Hongyu Wang, Xiang Ruan

In addition, to achieve accurate boundary inference and semantic enhancement, edge-aware feature maps in low-level layers and the predicted results of low resolution features are recursively embedded into the learning framework.

RGB Salient Object Detection Salient Object Detection

Sample-Specific SVM Learning for Person Re-Identification

no code implementations CVPR 2016 Ying Zhang, Baohua Li, Huchuan Lu, Atshushi Irie, Xiang Ruan

Person re-identification addresses the problem of matching people across disjoint camera views and extensive efforts have been made to seek either the robust feature representation or the discriminative matching metrics.

Dictionary Learning imbalanced classification +1

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

Salient Object Detection via Bootstrap Learning

no code implementations CVPR 2015 Na Tong, Huchuan Lu, Xiang Ruan, Ming-Hsuan Yang

Furthermore, we show that the proposed bootstrap learning approach can be easily applied to other bottom-up saliency models for significant improvement.

RGB Salient Object Detection Saliency Detection +1

Saliency Detection via Graph-Based Manifold Ranking

no code implementations CVPR 2013 Chuan Yang, Lihe Zhang, Huchuan Lu, Xiang Ruan, Ming-Hsuan Yang

The saliency of the image elements is defined based on their relevances to the given seeds or queries.

Saliency Detection

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