Search Results for author: Jianmin Ji

Found 12 papers, 2 papers with code

VPFNet: Improving 3D Object Detection with Virtual Point based LiDAR and Stereo Data Fusion

no code implementations29 Nov 2021 Hanqi Zhu, Jiajun Deng, Yu Zhang, Jianmin Ji, Qiuyu Mao, Houqiang Li, Yanyong Zhang

However, this approach often suffers from the mismatch between the resolution of point clouds and RGB images, leading to sub-optimal performance.

3D Object Detection Data Augmentation +1

Reinforcement Learning for Robot Navigation with Adaptive ExecutionDuration (AED) in a Semi-Markov Model

no code implementations13 Aug 2021 Yu'an Chen, Ruosong Ye, Ziyang Tao, Hongjian Liu, Guangda Chen, Jie Peng, Jun Ma, Yu Zhang, Yanyong Zhang, Jianmin Ji

Specifically, we formulate the navigation task as a Semi-Markov Decision Process (SMDP) problem to handle adaptive execution duration.

Robot Navigation

Neighbor-Vote: Improving Monocular 3D Object Detection through Neighbor Distance Voting

1 code implementation6 Jul 2021 Xiaomeng Chu, Jiajun Deng, Yao Li, Zhenxun Yuan, Yanyong Zhang, Jianmin Ji, Yu Zhang

As cameras are increasingly deployed in new application domains such as autonomous driving, performing 3D object detection on monocular images becomes an important task for visual scene understanding.

Autonomous Driving Monocular 3D Object Detection +2

Multi-Modal 3D Object Detection in Autonomous Driving: a Survey

no code implementations24 Jun 2021 Yingjie Wang, Qiuyu Mao, Hanqi Zhu, Yu Zhang, Jianmin Ji, Yanyong Zhang

In this survey, we first introduce the background of popular sensors for autonomous cars, including their common data representations as well as object detection networks developed for each type of sensor data.

3D Object Detection Autonomous Driving +2

3D Segmentation Learning from Sparse Annotations and Hierarchical Descriptors

no code implementations27 May 2021 Peng Yin, Lingyun Xu, Jianmin Ji, Sebastian Scherer, Howie Choset

One of the main obstacles to 3D semantic segmentation is the significant amount of endeavor required to generate expensive point-wise annotations for fully supervised training.

3D Semantic Segmentation

Neural networks behave as hash encoders: An empirical study

1 code implementation14 Jan 2021 Fengxiang He, Shiye Lei, Jianmin Ji, DaCheng Tao

We then define an {\it activation hash phase chart} to represent the space expanded by {model size}, training time, training sample size, and the encoding properties, which is divided into three canonical regions: {\it under-expressive regime}, {\it critically-expressive regime}, and {\it sufficiently-expressive regime}.

A Multi-Domain Feature Learning Method for Visual Place Recognition

no code implementations26 Feb 2019 Peng Yin, Lingyun Xu, Xueqian Li, Chen Yin, Yingli Li, Rangaprasad Arun Srivatsan, Lu Li, Jianmin Ji, Yuqing He

Visual Place Recognition (VPR) is an important component in both computer vision and robotics applications, thanks to its ability to determine whether a place has been visited and where specifically.

Visual Place Recognition

MRS-VPR: a multi-resolution sampling based global visual place recognition method

no code implementations26 Feb 2019 Peng Yin, Rangaprasad Arun Srivatsan, Yin Chen, Xueqian Li, Hongda Zhang, Lingyun Xu, Lu Li, Zhenzhong Jia, Jianmin Ji, Yuqing He

We propose MRS-VPR, a multi-resolution, sampling-based place recognition method, which can significantly improve the matching efficiency and accuracy in sequential matching.

Loop Closure Detection Visual Navigation +1

KDSL: a Knowledge-Driven Supervised Learning Framework for Word Sense Disambiguation

no code implementations28 Aug 2018 Shi Yin, Yi Zhou, Chenguang Li, Shangfei Wang, Jianmin Ji, Xiaoping Chen, Ruili Wang

We propose KDSL, a new word sense disambiguation (WSD) framework that utilizes knowledge to automatically generate sense-labeled data for supervised learning.

Word Sense Disambiguation

Well-Founded Operators for Normal Hybrid MKNF Knowledge Bases

no code implementations6 Jul 2017 Jianmin Ji, Fangfang Liu, Jia-Huai You

In this paper, we address this problem by formulating the notion of unfounded sets for nondisjunctive hybrid MKNF knowledge bases, based on which we propose and study two new well-founded operators.

Implementing Default and Autoepistemic Logics via the Logic of GK

no code implementations5 May 2014 Jianmin Ji, Hannes Strass

The logic of knowledge and justified assumptions, also known as logic of grounded knowledge (GK), was proposed by Lin and Shoham as a general logic for nonmonotonic reasoning.


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