Search Results for author: Chenglizhao Chen

Found 22 papers, 12 papers with code

Boundary-Guided Camouflaged Object Detection

1 code implementation2 Jul 2022 Yujia Sun, Shuo Wang, Chenglizhao Chen, Tian-Zhu Xiang

Camouflaged object detection (COD), segmenting objects that are elegantly blended into their surroundings, is a valuable yet challenging task.

object-detection Object Detection +1

A Novel Long-term Iterative Mining Scheme for Video Salient Object Detection

no code implementations20 Jun 2022 Chenglizhao Chen, Hengsen Wang, Yuming Fang, Chong Peng

The existing state-of-the-art (SOTA) video salient object detection (VSOD) models have widely followed short-term methodology, which dynamically determines the balance between spatial and temporal saliency fusion by solely considering the current consecutive limited frames.

object-detection Salient Object Detection +1

Log-based Sparse Nonnegative Matrix Factorization for Data Representation

no code implementations22 Apr 2022 Chong Peng, Yiqun Zhang, Yongyong Chen, Zhao Kang, Chenglizhao Chen, Qiang Cheng

Nonnegative matrix factorization (NMF) has been widely studied in recent years due to its effectiveness in representing nonnegative data with parts-based representations.

Hyperspectral Image Denoising Using Non-convex Local Low-rank and Sparse Separation with Spatial-Spectral Total Variation Regularization

no code implementations8 Jan 2022 Chong Peng, Yang Liu, Yongyong Chen, Xinxin Wu, Andrew Cheng, Zhao Kang, Chenglizhao Chen, Qiang Cheng

In this paper, we propose a novel nonconvex approach to robust principal component analysis for HSI denoising, which focuses on simultaneously developing more accurate approximations to both rank and column-wise sparsity for the low-rank and sparse components, respectively.

Hyperspectral Image Denoising Image Denoising

Weakly Supervised Visual-Auditory Fixation Prediction with Multigranularity Perception

1 code implementation27 Dec 2021 Guotao Wang, Chenglizhao Chen, Deng-Ping Fan, Aimin Hao, Hong Qin

Moreover, we distill knowledge from these regions to obtain complete new spatial-temporal-audio (STA) fixation prediction (FP) networks, enabling broad applications in cases where video tags are not available.

Video Saliency Detection

From Semantic Categories to Fixations: A Novel Weakly-Supervised Visual-Auditory Saliency Detection Approach

1 code implementation CVPR 2021 Guotao Wang, Chenglizhao Chen, Deng-Ping Fan, Aimin Hao, Hong Qin

Thanks to the rapid advances in the deep learning techniques and the wide availability of large-scale training sets, the performances of video saliency detection models have been improving steadily and significantly.

Video Saliency Detection

Mutual Graph Learning for Camouflaged Object Detection

1 code implementation CVPR 2021 Qiang Zhai, Xin Li, Fan Yang, Chenglizhao Chen, Hong Cheng, Deng-Ping Fan

Automatically detecting/segmenting object(s) that blend in with their surroundings is difficult for current models.

Graph Learning object-detection +1

Kernel Two-Dimensional Ridge Regression for Subspace Clustering

no code implementations3 Nov 2020 Chong Peng, Qian Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng

It directly uses 2D data as inputs such that the learning of representations benefits from inherent structures and relationships of the data.

Rethinking of the Image Salient Object Detection: Object-level Semantic Saliency Re-ranking First, Pixel-wise Saliency Refinement Latter

no code implementations10 Aug 2020 Zhen-Yu Wu, Shuai Li, Chenglizhao Chen, Aimin Hao, Hong Qin

In sharp contrast to the state-of-the-art (SOTA) methods that focus on learning pixel-wise saliency in "single image" using perceptual clues mainly, our method has investigated the "object-level semantic ranks between multiple images", of which the methodology is more consistent with the real human attention mechanism.

object-detection Re-Ranking +2

Knowing Depth Quality In Advance: A Depth Quality Assessment Method For RGB-D Salient Object Detection

1 code implementation7 Aug 2020 Xuehao Wang, Shuai Li, Chenglizhao Chen, Aimin Hao, Hong Qin

Previous RGB-D salient object detection (SOD) methods have widely adopted deep learning tools to automatically strike a trade-off between RGB and D (depth), whose key rationale is to take full advantage of their complementary nature, aiming for a much-improved SOD performance than that of using either of them solely.

object-detection RGB-D Salient Object Detection +2

A Deeper Look at Salient Object Detection: Bi-stream Network with a Small Training Dataset

no code implementations7 Aug 2020 Zhen-Yu Wu, Shuai Li, Chenglizhao Chen, Aimin Hao, Hong Qin

Compared with the conventional hand-crafted approaches, the deep learning based methods have achieved tremendous performance improvements by training exquisitely crafted fancy networks over large-scale training sets.

object-detection RGB Salient Object Detection +1

Data-Level Recombination and Lightweight Fusion Scheme for RGB-D Salient Object Detection

1 code implementation7 Aug 2020 Xuehao Wang, Shuai Li, Chenglizhao Chen, Yuming Fang, Aimin Hao, Hong Qin

Existing RGB-D salient object detection methods treat depth information as an independent component to complement its RGB part, and widely follow the bi-stream parallel network architecture.

object-detection RGB-D Salient Object Detection +1

Depth Quality Aware Salient Object Detection

1 code implementation7 Aug 2020 Chenglizhao Chen, Jipeng Wei, Chong Peng, Hong Qin

The existing fusion based RGB-D salient object detection methods usually adopt the bi-stream structure to strike the fusion trade-off between RGB and depth (D).

object-detection RGB-D Salient Object Detection +2

Recursive Multi-model Complementary Deep Fusion forRobust Salient Object Detection via Parallel Sub Networks

1 code implementation7 Aug 2020 Zhen-Yu Wu, Shuai Li, Chenglizhao Chen, Aimin Hao, Hong Qin

Finally, all these complementary multi-model deep features will be selectively fused to make high-performance salient object detections.

object-detection RGB Salient Object Detection +1

A Novel Video Salient Object Detection Method via Semi-supervised Motion Quality Perception

1 code implementation7 Aug 2020 Chenglizhao Chen, Jia Song, Chong Peng, Guodong Wang, Yuming Fang

Consequently, we can achieve a significant performance improvement by using this new training set to start a new round of network training.

object-detection Salient Object Detection +1

Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object Detection

1 code implementation7 Aug 2020 Chenglizhao Chen, Guotao Wang, Chong Peng, Dingwen Zhang, Yuming Fang, Hong Qin

In this way, even though the overall video saliency quality is heavily dependent on its spatial branch, however, the performance of the temporal branch still matter.

object-detection Salient Object Detection +2

Full Reference Screen Content Image Quality Assessment by Fusing Multi-level Structure Similarity

1 code implementation7 Aug 2020 Chenglizhao Chen, Hongmeng Zhao, Huan Yang, Chong Peng, Teng Yu

The screen content images (SCIs) usually comprise various content types with sharp edges, in which the artifacts or distortions can be well sensed by the vanilla structure similarity measurement in a full reference manner.

Image Quality Assessment

A Plug-and-play Scheme to Adapt Image Saliency Deep Model for Video Data

1 code implementation2 Aug 2020 Yunxiao Li, Shuai Li, Chenglizhao Chen, Aimin Hao, Hong Qin

With the rapid development of deep learning techniques, image saliency deep models trained solely by spatial information have occasionally achieved detection performance for video data comparable to that of the models trained by both spatial and temporal information.

Video Saliency Detection

Two-Dimensional Semi-Nonnegative Matrix Factorization for Clustering

no code implementations19 May 2020 Chong Peng, Zhilu Zhang, Zhao Kang, Chenglizhao Chen, Qiang Cheng

In particular, projection matrices are sought under the guidance of building new data representations, such that the spatial information is retained and projections are enhanced by the goal of clustering, which helps construct optimal projection directions.

Nonnegative Matrix Factorization with Local Similarity Learning

no code implementations9 Jul 2019 Chong Peng, Zhao Kang, Chenglizhao Chen, Qiang Cheng

Existing nonnegative matrix factorization methods focus on learning global structure of the data to construct basis and coefficient matrices, which ignores the local structure that commonly exists among data.

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