3 citations · 6 across the 7 of their papers we have counts for
7 papers
Indoor Obstacle Discovery on Reflective Ground via Monocular Camera
Feng Xue, Yicong Chang, Tianxi Wang +2
Visual obstacle discovery is a key step towards autonomous navigation of indoor mobile robots. Successful solutions have many applications in multiple scenes. One of the exceptions…
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…
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…
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…
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…