1 code implementation • 4 Apr 2024 • Jiahang Li, Peng Yun, Qijun Chen, Rui Fan
In this study, we take one step toward this new research area by exploring a feasible strategy to fully exploit VFM features for RGB-thermal scene parsing.
Ranked #1 on Thermal Image Segmentation on KP day-night
no code implementations • 19 Sep 2023 • Jiahang Li, Yikang Zhang, Peng Yun, Guangliang Zhou, Qijun Chen, Rui Fan
Additionally, we release SYN-UDTIRI, the first large-scale road scene parsing dataset that contains over 10, 407 RGB images, dense depth images, and the corresponding pixel-level annotations for both freespace and road defects of different shapes and sizes.
1 code implementation • 4 Jul 2022 • Jun Cen, Peng Yun, Shiwei Zhang, Junhao Cai, Di Luan, Michael Yu Wang, Ming Liu, Mingqian Tang
Current methods for LIDAR semantic segmentation are not robust enough for real-world applications, e. g., autonomous driving, since it is closed-set and static.
no code implementations • 2 Dec 2021 • Jun Cen, Peng Yun, Junhao Cai, Michael Yu Wang, Ming Liu
The first step is solved by the finding that unknown objects are often classified as known objects with low confidence, and we show that the Euclidean distance sum based on metric learning is a better confidence score than the naive softmax probability to differentiate unknown objects from known objects.
1 code implementation • ICCV 2021 • Jun Cen, Peng Yun, Junhao Cai, Michael Yu Wang, Ming Liu
Incrementally learning these OOD objects with few annotations is an ideal way to enlarge the knowledge base of the deep learning models.
no code implementations • 24 Mar 2021 • Jianhao Jiao, Yilong Zhu, Haoyang Ye, Huaiyang Huang, Peng Yun, Linxin Jiang, Lujia Wang, Ming Liu
Modern LiDAR-SLAM (L-SLAM) systems have shown excellent results in large-scale, real-world scenarios.
no code implementations • 2 Oct 2020 • M Usman Maqbool Bhutta, Shoaib Aslam, Peng Yun, Jianhao Jiao, Ming Liu
We present a robust semi-supervised learning framework for intelligent micro-scaled localization and classification of defects on a 16K pixel image of smartphone glass.
2 code implementations • 29 Sep 2020 • Jianhao Jiao, Peng Yun, Lei Tai, Ming Liu
To minimize the detrimental effect of extrinsic perturbation, we propagate an uncertainty prior on each point of input point clouds, and use this information to boost an approach for 3D geometric tasks.
no code implementations • 16 Apr 2020 • Tianyu Liu, Qinghai Liao, Lu Gan, Fulong Ma, Jie Cheng, Xupeng Xie, Zhe Wang, Yingbing Chen, Yilong Zhu, Shuyang Zhang, Zhengyong Chen, Yang Liu, Meng Xie, Yang Yu, Zitong Guo, Guang Li, Peidong Yuan, Dong Han, Yuying Chen, Haoyang Ye, Jianhao Jiao, Peng Yun, Zhenhua Xu, Hengli Wang, Huaiyang Huang, Sukai Wang, Peide Cai, Yuxiang Sun, Yandong Liu, Lujia Wang, Ming Liu
Moreover, many countries have imposed tough lockdown measures to reduce the virus transmission (e. g., retail, catering) during the pandemic, which causes inconveniences for human daily life.
1 code implementation • 3 Mar 2019 • Lei Tai, Peng Yun, Yuying Chen, Congcong Liu, Haoyang Ye, Ming Liu
End-to-end visual-based imitation learning has been widely applied in autonomous driving.
1 code implementation • 17 Sep 2018 • Peng Yun, Lei Tai, Yu-An Wang, Chengju Liu, Ming Liu
Inspired by the recent use of focal loss in image-based object detection, we extend this hard-mining improvement of binary cross entropy to point-cloud-based object detection and conduct experiments to show its performance based on two different 3D detectors: 3D-FCN and VoxelNet.
3 code implementations • 17 Jul 2018 • Yu-An Wang, Tianyue Shi, Peng Yun, Lei Tai, Ming Liu
We take the spherical image, which is transformed from the 3D LiDAR point clouds, as input of the convolutional neural networks (CNNs) to predict the point-wise semantic map.
no code implementations • 1 Feb 2018 • Jingwei Zhang, Lei Tai, Peng Yun, Yufeng Xiong, Ming Liu, Joschka Boedecker, Wolfram Burgard
In this paper, we deal with the reality gap from a novel perspective, targeting transferring Deep Reinforcement Learning (DRL) policies learned in simulated environments to the real-world domain for visual control tasks.