activity
20192022
most citedContext-Constrained Accurate Contour Extraction for Occlusion Edge Detection

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.RO2022

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…

cs.CV2021

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…

cs.CV2019

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…

cs.CV2019

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…

cs.CV20192 cited

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…