no code implementations • 22 Feb 2021 • Xiaolong Guo, Xiaosong Lan, Kunfeng Wang, Shuxiao Li
Instance segmentation aims to locate targets in the image and segment each target area at pixel level, which is one of the most important tasks in computer vision.
1 code implementation • 10 Dec 2019 • Yonglin Tian, Lichao Huang, Xuesong Li, Kunfeng Wang, Zilei Wang, Fei-Yue Wang
Varying density of point clouds increases the difficulty of 3D detection.
no code implementations • 10 Oct 2019 • Yonglin Tian, Kunfeng Wang, Yuang Wang, Yulin Tian, Zilei Wang, Fei-Yue Wang
We adopt different modalities of LiDAR data to generate richer features and present an adaptive and azimuth-aware network to aggregate local features from image, bird's eye view maps and point cloud.
no code implementations • 14 Feb 2018 • Kunfeng Wang, Chao Gou, Fei-Yue Wang
Secondly, multiple heterogeneous features (including brightness variation, chromaticity variation, and texture variation) are extracted by comparing the input frame with the background model, and a multi-source learning strategy is designed to online estimate the probability distributions for both foreground and background.
1 code implementation • 23 Dec 2017 • Wenwen Zhang, Kunfeng Wang, Hua Qu, Jihong Zhao, Fei-Yue Wang
In order to make the generic scene pedestrian detectors work well in specific scenes, the labeled data from specific scenes are needed to adapt the models to the specific scenes.
no code implementations • 22 Dec 2017 • Yonglin Tian, Xuan Li, Kunfeng Wang, Fei-Yue Wang
In the area of computer vision, deep learning has produced a variety of state-of-the-art models that rely on massive labeled data.
no code implementations • 22 Dec 2017 • Xuan Li, Kunfeng Wang, Yonglin Tian, Lan Yan, Fei-Yue Wang
As a result, we present a viable implementation pipeline for constructing large-scale artificial scenes for traffic vision research.