224 citations · 2.3k across the 117 of their papers we have counts for
18 papers · 1 filter
DUT-LFSaliency: Versatile Dataset and Light Field-to-RGB Saliency Detection
Yongri Piao, Zhengkun Rong, Shuang Xu +2
Light field data exhibit favorable characteristics conducive to saliency detection. The success of learning-based light field saliency detection is heavily dependent on how a compr…
Multi-modal Visual Tracking: Review and Experimental Comparison
Pengyu Zhang, Dong Wang, Huchuan Lu
Visual object tracking, as a fundamental task in computer vision, has drawn much attention in recent years. To extend trackers to a wider range of applications, researchers have in…
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
Bin Yan, Xinyu Zhang, Dong Wang +2
Visual object tracking aims to precisely estimate the bounding box for the given target, which is a challenging problem due to factors such as deformation and occlusion. Many recen…
CR-Fill: Generative Image Inpainting with Auxiliary Contexutal Reconstruction
Yu Zeng, Zhe Lin, Huchuan Lu +1
Recent deep generative inpainting methods use attention layers to allow the generator to explicitly borrow feature patches from the known region to complete a missing region. Due t…
Coherent Loss: A Generic Framework for Stable Video Segmentation
Mingyang Qian, Yi Fu, Xiao Tan +5
Video segmentation approaches are of great importance for numerous vision tasks especially in video manipulation for entertainment. Due to the challenges associated with acquiring…
Suppress and Balance: A Simple Gated Network for Salient Object Detection
Xiaoqi Zhao, Youwei Pang, Lihe Zhang +2
Most salient object detection approaches use U-Net or feature pyramid networks (FPN) as their basic structures. These methods ignore two key problems when the encoder exchanges inf…
Accurate RGB-D Salient Object Detection via Collaborative Learning
Wei Ji, Jingjing Li, Miao Zhang +2
Benefiting from the spatial cues embedded in depth images, recent progress on RGB-D saliency detection shows impressive ability on some challenge scenarios. However, there are stil…
Multi-scale Interactive Network for Salient Object Detection
Youwei Pang, Xiaoqi Zhao, Lihe Zhang +1
Deep-learning based salient object detection methods achieve great progress. However, the variable scale and unknown category of salient objects are great challenges all the time.…
Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detection
Youwei Pang, Lihe Zhang, Xiaoqi Zhao +1
The main purpose of RGB-D salient object detection (SOD) is how to better integrate and utilize cross-modal fusion information. In this paper, we explore these issues from a new pe…
A Single Stream Network for Robust and Real-time RGB-D Salient Object Detection
Xiaoqi Zhao, Lihe Zhang, Youwei Pang +2
Existing RGB-D salient object detection (SOD) approaches concentrate on the cross-modal fusion between the RGB stream and the depth stream. They do not deeply explore the effect of…
Jointly Modeling Motion and Appearance Cues for Robust RGB-T Tracking
Pengyu Zhang, Jie Zhao, Dong Wang +2
In this study, we propose a novel RGB-T tracking framework by jointly modeling both appearance and motion cues. First, to obtain a robust appearance model, we develop a novel late…
Alpha-Refine: Boosting Tracking Performance by Precise Bounding Box Estimation
Bin Yan, Dong Wang, Huchuan Lu +1
In recent years, the multiple-stage strategy has become a popular trend for visual tracking. This strategy first utilizes a base tracker to coarsely locate the target and then expl…
Synergistic saliency and depth prediction for RGB-D saliency detection
Yue Wang, Yuke Li, James H. Elder +3
Depth information available from an RGB-D camera can be useful in segmenting salient objects when figure/ground cues from RGB channels are weak. This has motivated the development…
High-Resolution Image Inpainting with Iterative Confidence Feedback and Guided Upsampling
Yu Zeng, Zhe Lin, Jimei Yang +3
Existing image inpainting methods often produce artifacts when dealing with large holes in real applications. To address this challenge, we propose an iterative inpainting method w…
High-Performance Long-Term Tracking with Meta-Updater
Kenan Dai, Yunhua Zhang, Dong Wang +3
Long-term visual tracking has drawn increasing attention because it is much closer to practical applications than short-term tracking. Most top-ranked long-term trackers adopt the…
Pose-guided Visible Part Matching for Occluded Person ReID
Shang Gao, Jingya Wang, Huchuan Lu +1
Occluded person re-identification is a challenging task as the appearance varies substantially with various obstacles, especially in the crowd scenario. To address this issue, we p…
Cooling-Shrinking Attack: Blinding the Tracker with Imperceptible Noises
Bin Yan, Dong Wang, Huchuan Lu +1
Adversarial attack of CNN aims at deceiving models to misbehave by adding imperceptible perturbations to images. This feature facilitates to understand neural networks deeply and t…
When Relation Networks meet GANs: Relation GANs with Triplet Loss
Runmin Wu, Kunyao Zhang, Lijun Wang +4
Though recent research has achieved remarkable progress in generating realistic images with generative adversarial networks (GANs), the lack of training stability is still a linger…