Search Results for author: Qingquan Li

Found 14 papers, 2 papers with code

MUSER: A Multi-View Similar Case Retrieval Dataset

1 code implementation24 Oct 2023 Qingquan Li, Yiran Hu, Feng Yao, Chaojun Xiao, Zhiyuan Liu, Maosong Sun, Weixing Shen

Furthermore, the case similarities are typically measured solely by the textual semantics of the fact descriptions, which may fail to capture the full complexity of legal cases from the perspective of legal knowledge.

Fairness Retrieval +3

Optimized Views Photogrammetry: Precision Analysis and A Large-scale Case Study in Qingdao

no code implementations24 Jun 2022 Qingquan Li, Wenshuai Yu, San Jiang

Besides, the case study in Qingdao city verifies that optimized views photogrammetry can be a reliable and powerful solution for the large-scale 3D modeling in complex urban scenes.

Trajectory Planning

Parallel Structure from Motion for UAV Images via Weighted Connected Dominating Set

no code implementations23 Jun 2022 San Jiang, Qingquan Li, Wanshou Jiang, Wu Chen

This paper proposes an algorithm to extract the global model for cluster merging and designs a parallel SfM solution to achieve efficient and accurate UAV image orientation.

Retrieval

Improving short-term bike sharing demand forecast through an irregular convolutional neural network

no code implementations9 Feb 2022 Xinyu Li, Yang Xu, Xiaohu Zhang, Wenzhong Shi, Yang Yue, Qingquan Li

As an important task for the management of bike sharing systems, accurate forecast of travel demand could facilitate dispatch and relocation of bicycles to improve user satisfaction.

Management

An adaptive Origin-Destination flows cluster-detecting method to identify urban mobility trends

no code implementations10 Jun 2021 Mengyuan Fang, Luliang Tang, Zihan Kan, Xue Yang, Tao Pei, Qingquan Li, Chaokui Li

As an important spatial analysis approach, the clustering methods of point events have been extended to OD flows to identify the dominant trends and spatial structures of urban mobility.

Clustering

Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications

no code implementations9 Nov 2020 Qing Li, Jiasong Zhu, Jun Liu, Rui Cao, Qingquan Li, Sen Jia, Guoping Qiu

Despite the rapid progress in this topic, there are lacking of a comprehensive review, which is needed to summarize the current progress and provide the future directions.

Depth Prediction Indoor Localization +2

Enhancing Remote Sensing Image Retrieval with Triplet Deep Metric Learning Network

no code implementations15 Feb 2019 Rui Cao, Qian Zhang, Jiasong Zhu, Qing Li, Qingquan Li, Bozhi Liu, Guoping Qiu

With the rapid growing of remotely sensed imagery data, there is a high demand for effective and efficient image retrieval tools to manage and exploit such data.

Image Retrieval Metric Learning +1

Deep Learning-Based Gait Recognition Using Smartphones in the Wild

1 code implementation1 Nov 2018 Qin Zou, Yanling Wang, Qian Wang, Yi Zhao, Qingquan Li

Specifically, a hybrid deep neural network is proposed for robust gait feature representation, where features in the space and time domains are successively abstracted by a convolutional neural network and a recurrent neural network.

Gait Recognition Person Identification

Robust Gait Recognition by Integrating Inertial and RGBD Sensors

no code implementations31 Oct 2016 Qin Zou, Lihao Ni, Qian Wang, Qingquan Li, Song Wang

We propose two new algorithms, namely EigenGait and TrajGait, to extract gait features from the inertial data and the RGBD (color and depth) data, respectively.

Gait Recognition Person Identification

Who Leads the Clothing Fashion: Style, Color, or Texture? A Computational Study

no code implementations26 Aug 2016 Qin Zou, Zheng Zhang, Qian Wang, Qingquan Li, Long Chen, Song Wang

Specifically, a classification-based model is proposed to quantify the influence of different visual stimuli, in which each visual stimulus's influence is quantified by its corresponding accuracy in fashion classification.

General Classification

LOAD: Local Orientation Adaptive Descriptor for Texture and Material Classification

no code implementations22 Apr 2015 Xianbiao Qi, Guoying Zhao, Linlin Shen, Qingquan Li, Matti Pietikainen

It is worth to mention that we achieve a 65. 4\% classification accuracy-- which is, to the best of our knowledge, the highest record by far --on Flickr Material Database by using a single feature.

General Classification Material Classification +2

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