3 citations · 7 across the 12 of their papers we have counts for
13 papers
Unknown Sniffer for Object Detection: Don't Turn a Blind Eye to Unknown Objects
Wenteng Liang, Feng Xue, Yihao Liu +2
The recently proposed open-world object and open-set detection have achieved a breakthrough in finding never-seen-before objects and distinguishing them from known ones. However, t…
Mask Reference Image Quality Assessment
Pengxiang Xiao, Shuai He, Limin Liu +1
Understanding semantic information is an essential step in knowing what is being learned in both full-reference (FR) and no-reference (NR) image quality assessment (IQA) methods. H…
Balanced Line Coverage in Large-scale Urban Scene
Hangsong Su, Feng Xue, Runze Guo +1
Line coverage is to cover linear infrastructure modeled as 1D segments by robots, which received attention in recent years. With the increasing urbanization, the area of the city a…
MARF: Multiscale Adaptive-switch Random Forest for Leg Detection with 2D Laser Scanners
Tianxi Wang, Feng Xue, Yu Zhou +1
For the 2D laser-based tasks, e.g., people detection and people tracking, leg detection is usually the first step. Thus, it carries great weight in determining the performance of p…
Monocular Depth Distribution Alignment with Low Computation
Fei Sheng, Feng Xue, Yicong Chang +2
The performance of monocular depth estimation generally depends on the amount of parameters and computational cost. It leads to a large accuracy contrast between light-weight netwo…
Fast Road Segmentation via Uncertainty-aware Symmetric Network
Yicong Chang, Feng Xue, Fei Sheng +2
The high performance of RGB-D based road segmentation methods contrasts with their rare application in commercial autonomous driving, which is owing to two reasons: 1) the prior me…
Tiny Obstacle Discovery by Occlusion-Aware Multilayer Regression
Feng Xue, Anlong Ming, Yu Zhou
Edges are the fundamental visual element for discovering tiny obstacles using a monocular camera. Nevertheless, tiny obstacles often have weak and inconsistent edge cues due to var…
MT-ORL: Multi-Task Occlusion Relationship Learning
Panhe Feng, Qi She, Lei Zhu +7
Retrieving occlusion relation among objects in a single image is challenging due to sparsity of boundaries in image. We observe two key issues in existing works: firstly, lack of a…
Boundary-induced and scene-aggregated network for monocular depth prediction
Feng Xue, Junfeng Cao, Yu Zhou +3
Monocular depth prediction is an important task in scene understanding. It aims to predict the dense depth of a single RGB image. With the development of deep learning, the perform…
DDNet: Dual-path Decoder Network for Occlusion Relationship Reasoning
Panhe Feng, Xuejing Kang, Lizhu Ye +3
Occlusion relationship reasoning based on convolution neural networks consists of two subtasks: occlusion boundary extraction and occlusion orientation inference. Due to the essent…
Occlusion-shared and Feature-separated Network for Occlusion Relationship Reasoning
Rui Lu, Feng Xue, Menghan Zhou +2
Occlusion relationship reasoning demands closed contour to express the object, and orientation of each contour pixel to describe the order relationship between objects. Current CNN…
A Novel Multi-layer Framework for Tiny Obstacle Discovery
Feng Xue, Anlong Ming, Menghan Zhou +1
For tiny obstacle discovery in a monocular image, edge is a fundamental visual element. Nevertheless, because of various reasons, e.g., noise and similar color distribution with ba…
Context-Constrained Accurate Contour Extraction for Occlusion Edge Detection
Rui Lu, Menghan Zhou, Anlong Ming +1
Occlusion edge detection requires both accurate locations and context constraints of the contour. Existing CNN-based pipeline does not utilize adaptive methods to filter the noise…