no code implementations • ACL 2022 • Runxin Sun, Shizhu He, Chong Zhu, Yaohan He, Jinlong Li, Jun Zhao, Kang Liu
Text-to-SQL aims to parse natural language questions into SQL queries, which is valuable in providing an easy interface to access large databases.
no code implementations • Findings (NAACL) 2022 • Le Qi, Yu Zhang, Qingyu Yin, Guidong Zheng, Wen Junjie, Jinlong Li, Ting Liu
In this process, there are two kinds of critical information that are commonly employed: the representation information of original questions and the interactive information between pairs of questions.
no code implementations • EMNLP 2021 • Yiming Ju, Yuanzhe Zhang, Zhixing Tian, Kang Liu, Xiaohuan Cao, Wenting Zhao, Jinlong Li, Jun Zhao
Multiple-choice MRC is one of the most studied tasks in MRC due to the convenience of evaluation and the flexibility of answer format.
no code implementations • 7 Apr 2024 • Jinlong Li, Baolu Li, Zhengzhong Tu, Xinyu Liu, Qing Guo, Felix Juefei-Xu, Runsheng Xu, Hongkai Yu
Vision-centric perception systems for autonomous driving have gained considerable attention recently due to their cost-effectiveness and scalability, especially compared to LiDAR-based systems.
no code implementations • 17 Mar 2024 • Baolu Li, Jinlong Li, Xinyu Liu, Runsheng Xu, Zhengzhong Tu, Jiacheng Guo, Xiaopeng Li, Hongkai Yu
Current LiDAR-based Vehicle-to-Everything (V2X) multi-agent perception systems have shown the significant success on 3D object detection.
no code implementations • 6 Feb 2024 • Jinlong Li, Baolu Li, Xinyu Liu, Runsheng Xu, Jiaqi Ma, Hongkai Yu
However, the data source to train the various agents is independent and private in each company, leading to the Distribution Gap of different private data for training distinct agents in multi-agent perception system.
no code implementations • 30 Jan 2024 • Jinlong Li, Baolu Li, Xinyu Liu, Jianwu Fang, Felix Juefei-Xu, Qing Guo, Hongkai Yu
The multi-agent perception system collects visual data from sensors located on various agents and leverages their relative poses determined by GPS signals to effectively fuse information, mitigating the limitations of single-agent sensing, such as occlusion.
no code implementations • 3 Dec 2023 • AlMotasem Bellah Al Ajlouni, Jinlong Li
This underscores the potential of CEScore as a simple and effective metric for assessing the overall quality of SR models.
no code implementations • 27 Nov 2023 • Baolu Li, Ping Liu, Lan Fu, Jinlong Li, Jianwu Fang, Zhigang Xu, Hongkai Yu
Vehicle Re-identification (Re-ID) has been broadly studied in the last decade; however, the different camera view angle leading to confused discrimination in the feature subspace for the vehicles of various poses, is still challenging for the Vehicle Re-ID models in the real world.
no code implementations • 18 Jul 2023 • Jinlong Li, Runsheng Xu, Jin Ma, Qin Zou, Jiaqi Ma, Hongkai Yu
To bridge the domain gap and improve the performance of object detectionin foggy and rainy weather, this paper presents a novel framework for domain-adaptive object detection.
no code implementations • 16 Jul 2023 • Jinlong Li, Runsheng Xu, Xinyu Liu, Baolu Li, Qin Zou, Jiaqi Ma, Hongkai Yu
We investigate the effects of these two types of domain gaps and propose a novel uncertainty-aware vision transformer to effectively relief the Deployment Gap and an agent-based feature adaptation module with inter-agent and ego-agent discriminators to reduce the Feature Gap.
no code implementations • 30 Jun 2023 • Huiming Sun, Lan Fu, Jinlong Li, Qing Guo, Zibo Meng, Tianyun Zhang, Yuewei Lin, Hongkai Yu
Furthermore, we design DefenseNet as a learn-able pre-processing to the adversarial cloudy images so as to preserve the performance of the deep learning based remote sensing SOD model, without tuning the already deployed deep SOD model.
no code implementations • 26 Jun 2023 • Xinyu Liu, Jinlong Li, Jin Ma, Huiming Sun, Zhigang Xu, Tianyun Zhang, Hongkai Yu
To the best of our knowledge, this paper represents the first comprehensive survey on the topic of the deep transfer learning for intelligent vehicle perception.
no code implementations • 22 Jun 2023 • Jin Ma, Jinlong Li, Qing Guo, Tianyun Zhang, Yuewei Lin, Hongkai Yu
The emergence of different sensors (Near-Infrared, Depth, etc.)
1 code implementation • CVPR 2023 • Runsheng Xu, Xin Xia, Jinlong Li, Hanzhao Li, Shuo Zhang, Zhengzhong Tu, Zonglin Meng, Hao Xiang, Xiaoyu Dong, Rui Song, Hongkai Yu, Bolei Zhou, Jiaqi Ma
To facilitate the development of cooperative perception, we present V2V4Real, the first large-scale real-world multi-modal dataset for V2V perception.
no code implementations • 10 Feb 2023 • Lan Fu, Zhiyuan Liu, Jinlong Li, Jeff Simmons, Hongkai Yu, Song Wang
Accurate detection of large-scale, elliptical-shape fibers, including their parameters of center, orientation and major/minor axes, on the 2D cross-sectioned image slices is very important for characterizing the underlying cylinder 3D structures in microscopic material images.
1 code implementation • 16 Dec 2022 • Jinlong Li, Runsheng Xu, Xinyu Liu, Jin Ma, Zicheng Chi, Jiaqi Ma, Hongkai Yu
Due to the beneficial Vehicle-to-Vehicle (V2V) communication, the deep learning based features from other agents can be shared to the ego vehicle so as to improve the perception of the ego vehicle.
no code implementations • 9 Nov 2022 • Talha Azfar, Jinlong Li, Hongkai Yu, Ruey Long Cheu, Yisheng Lv, Ruimin Ke
This paper conducted an extensive literature review on the applications of computer vision in ITS and AD, and discusses challenges related to data, models, and complex urban environments.
1 code implementation • 27 Oct 2022 • Jinlong Li, Runsheng Xu, Jin Ma, Qin Zou, Jiaqi Ma, Hongkai Yu
This paper proposes a novel domain adaptive object detection framework for autonomous driving under foggy weather.
1 code implementation • 16 Oct 2022 • Runsheng Xu, Jinlong Li, Xiaoyu Dong, Hongkai Yu, Jiaqi Ma
Existing multi-agent perception algorithms usually select to share deep neural features extracted from raw sensing data between agents, achieving a trade-off between accuracy and communication bandwidth limit.
1 code implementation • 16 Sep 2022 • Jinlong Li, Zequn Jie, Xu Wang, Xiaolin Wei, Lin Ma
To tackle with this issue, this paper proposes an Expansion and Shrinkage scheme based on the offset learning in the deformable convolution, to sequentially improve the recall and precision of the located object in the two respective stages.
1 code implementation • 16 Sep 2022 • Jinlong Li, Zequn Jie, Xu Wang, Yu Zhou, Xiaolin Wei, Lin Ma
"Progressive Patch Learning" further extends the feature destruction and patch learning to multi-level granularities in a progressive manner.
Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation
1 code implementation • 5 Jul 2022 • Adnan Ali, Jinlong Li
Self-Supervised learning aims to eliminate the need for expensive annotation in graph representation learning, where graph contrastive learning (GCL) is trained with the self-supervision signals containing data-data pairs.
1 code implementation • 4 May 2022 • Runsheng Xu, Zhengzhong Tu, Yuanqi Du, Xiaoyu Dong, Jinlong Li, Zibo Meng, Jiaqi Ma, Alan Bovik, Hongkai Yu
Our proposed framework consists of three modules: a restoration sub-network that conducts restoration from degradations, a similarity network that performs color histogram matching and color transfer, and a colorization subnet that learns to predict the chroma elements of images conditioned on chromatic reference signals.
no code implementations • 22 Mar 2022 • Guangqian Yang, Yibing Zhan, Jinlong Li, Baosheng Yu, Liu Liu, Fengxiang He
In this paper, we analyze the adversarial attack on graphs from the perspective of feature smoothness which further contributes to an efficient new adversarial defensive algorithm for GNNs.
no code implementations • 5 Feb 2022 • Runsheng Xu, Zhengzhong Tu, Yuanqi Du, Xiaoyu Dong, Jinlong Li, Zibo Meng, Jiaqi Ma, Hongkai Yu
Renovating the memories in old photos is an intriguing research topic in computer vision fields.
no code implementations • 5 Jan 2022 • Xu Zhang, Jian Yang, Haoyang Huang, Shuming Ma, Dongdong Zhang, Jinlong Li, Furu Wei
Existing document-level neural machine translation (NMT) models have sufficiently explored different context settings to provide guidance for target generation.
3 code implementations • 16 Sep 2021 • Runsheng Xu, Hao Xiang, Xin Xia, Xu Han, Jinlong Li, Jiaqi Ma
We then construct a comprehensive benchmark with a total of 16 implemented models to evaluate several information fusion strategies~(i. e. early, late, and intermediate fusion) with state-of-the-art LiDAR detection algorithms.
Ranked #2 on 3D Object Detection on OPV2V
1 code implementation • ACL 2021 • Xin Xin, Jinlong Li, Zeqi Tan
In this paper, we study the task of graph-based constituent parsing in the setting that binarization is not conducted as a pre-processing step, where a constituent tree may consist of nodes with more than two children.
Ranked #3 on Constituency Parsing on CTB5
1 code implementation • 19 May 2021 • Shengfei Lyu, Xingyu Wu, Jinlong Li, Qiuju Chen, Huanhuan Chen
Deep neural networks such as BERT have made great progress in relation classification.
no code implementations • 11 May 2021 • Lan Fu, Hongkai Yu, Felix Juefei-Xu, Jinlong Li, Qing Guo, Song Wang
As one of the state-of-the-art perception approaches, detecting the interested objects in each frame of video surveillance is widely desired by ITS.
no code implementations • 15 Dec 2020 • Peng Zhang, Jinlong Li, Tengfei Li, Huanhuan Chen
To handle different types of Many-Objective Optimization Problems (MaOPs), Many-Objective Evolutionary Algorithms (MaOEAs) need to simultaneously maintain convergence and population diversity in the high-dimensional objective space.
no code implementations • 30 Jun 2020 • Haiwei Huang, Jinlong Li, Huimin He, Huanhuan Chen
Network embedding is a very important method for network data.
no code implementations • 5 Mar 2020 • Mengxiao Hu, Jinlong Li, Maolin Hu, Tao Hu
In conditional Generative Adversarial Networks (cGANs), when two different initial noises are concatenated with the same conditional information, the distance between their outputs is relatively smaller, which makes minor modes likely to collapse into large modes.
no code implementations • 27 Dec 2019 • Weibo Shu, Yaqiang Yao, Shengfei Lyu, Jinlong Li, Huanhuan Chen
In the research area of time series classification, the ensemble shapelet transform algorithm is one of state-of-the-art algorithms for classification.
no code implementations • 21 May 2019 • Mengxiao Hu, Jinlong Li
For machine learning task, lacking sufficient samples mean the trained model has low confidence to approach the ground truth function.