434 citations · 681 across the 14 of their papers we have counts for
14 papers
Boosting Multi-View Stereo with Depth Foundation Model in the Absence of Real-World Labels
Jie Zhu, Bo Peng, Zhe Zhang +2
Learning-based Multi-View Stereo (MVS) methods have made remarkable progress in recent years. However, how to effectively train the network without using real-world labels remains…
Stereo Image Coding for Machines with Joint Visual Feature Compression
Dengchao Jin, Jianjun Lei, Bo Peng +3
2D image coding for machines (ICM) has achieved great success in coding efficiency, while less effort has been devoted to stereo image fields. To promote the efficiency of stereo i…
Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360° Omnidirectional Image
Runmin Cong, Ke Huang, Jianjun Lei +3
Salient object detection (SOD) aims to determine the most visually attractive objects in an image. With the development of virtual reality technology, 360° omnidirectional image ha…
PSNet: Parallel Symmetric Network for Video Salient Object Detection
Runmin Cong, Weiyu Song, Jianjun Lei +3
For the video salient object detection (VSOD) task, how to excavate the information from the appearance modality and the motion modality has always been a topic of great concern. T…
Multi-View Stereo with Transformer
Jie Zhu, Bo Peng, Wanqing Li +3
This paper proposes a network, referred to as MVSTR, for Multi-View Stereo (MVS). It is built upon Transformer and is capable of extracting dense features with global context and 3…
Novel View Synthesis from a Single Image via Unsupervised learning
Bingzheng Liu, Jianjun Lei, Bo Peng +3
View synthesis aims to generate novel views from one or more given source views. Although existing methods have achieved promising performance, they usually require paired views of…
Video Compression Coding via Colorization: A Generative Adversarial Network (GAN)-Based Approach
Zhaoqing Pan, Feng Yuan, Jianjun Lei +1
Under the limited storage, computing and network bandwidth resources, the video compression coding technology plays an important role for visual communication. To efficiently compr…
Semi-Heterogeneous Three-Way Joint Embedding Network for Sketch-Based Image Retrieval
Jianjun Lei, Yuxin Song, Bo Peng +3
Sketch-based image retrieval (SBIR) is a challenging task due to the large cross-domain gap between sketches and natural images. How to align abstract sketches and natural images i…
HSCS: Hierarchical Sparsity Based Co-saliency Detection for RGBD Images
Runmin Cong, Jianjun Lei, Huazhu Fu +3
Co-saliency detection aims to discover common and salient objects in an image group containing more than two relevant images. Moreover, depth information has been demonstrated to b…
Person Re-Identification by Semantic Region Representation and Topology Constraint
Jianjun Lei, Lijie Niu, Huazhu Fu +3
Person re-identification is a popular research topic which aims at matching the specific person in a multi-camera network automatically. Feature representation and metric learning…
Review of Visual Saliency Detection with Comprehensive Information
Runmin Cong, Jianjun Lei, Huazhu Fu +3
Visual saliency detection model simulates the human visual system to perceive the scene, and has been widely used in many vision tasks. With the acquisition technology development,…
An Iterative Co-Saliency Framework for RGBD Images
Runmin Cong, Jianjun Lei, Huazhu Fu +4
As a newly emerging and significant topic in computer vision community, co-saliency detection aims at discovering the common salient objects in multiple related images. The existin…
Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion
Runmin Cong, Jianjun Lei, Changqing Zhang +3
Stereoscopic perception is an important part of human visual system that allows the brain to perceive depth. However, depth information has not been well explored in existing salie…
Co-saliency Detection for RGBD Images Based on Multi-constraint Feature Matching and Cross Label Propagation
Runmin Cong, Jianjun Lei, Huazhu Fu +3
Co-saliency detection aims at extracting the common salient regions from an image group containing two or more relevant images. It is a newly emerging topic in computer vision comm…