no code implementations • 15 Jan 2018 • Ao Zhang, Nan Li, Jian Pu, Jun Wang, Junchi Yan, Hongyuan Zha
Learning a classifier with control on the false-positive rate plays a critical role in many machine learning applications.
no code implementations • 26 Jun 2018 • Li Wang, Weiyuan Shao, Yao Lu, Hao Ye, Jian Pu, Yingbin Zheng
Crowd counting is one of the core tasks in various surveillance applications.
no code implementations • 28 Apr 2021 • Jie Chen, Shouzhen Chen, Mingyuan Bai, Jian Pu, Junping Zhang, Junbin Gao
In this paper, we consider the label dependency of graph nodes and propose a decoupling attention mechanism to learn both hard and soft attention.
no code implementations • 30 May 2022 • Jie Chen, Weiqi Liu, Zhizhong Huang, Junbin Gao, Junping Zhang, Jian Pu
The performance of GNNs degrades as they become deeper due to the over-smoothing.
Ranked #9 on Node Classification on Squirrel
no code implementations • 30 Nov 2022 • Zizhang Wu, Yunzhe Wu, Jian Pu, Xianzhi Li, Xiaoquan Wang
Specifically, we leverage intermediate features and responses for knowledge distillation.
no code implementations • 21 Feb 2023 • Zizhang Wu, Yuanzhu Gan, Lei Wang, Guilian Chen, Jian Pu
Monocular 3D object detection reveals an economical but challenging task in autonomous driving.
no code implementations • 21 Feb 2023 • Zizhang Wu, Guilian Chen, Yuanzhu Gan, Lei Wang, Jian Pu
To achieve so, we inject the semantic alignment into the radar features via the semantic-aligned radar encoder (SARE) to produce image-guided radar features.
Ranked #7 on 3D Object Detection on nuscenes Camera-Radar
no code implementations • 12 May 2023 • Zizhang Wu, Zhuozheng Li, Zhi-Gang Fan, Yunzhe Wu, Yuanzhu Gan, Jian Pu, Xianzhi Li
During the refinement process, context-aware temporal attention (CTA) is developed to capture the global temporal-context correlations to maintain the feature consistency and estimation integrity of moving objects.
no code implementations • 19 Jun 2023 • Xianhui Cheng, Shoumeng Qiu, Zhikang Zou, Jian Pu, xiangyang xue
In this paper, we propose a framework named the Adaptive Distance Interval Separation Network (ADISN) that adopts a novel perspective on understanding depth maps, as a form that lies between LiDAR and images.
no code implementations • 19 Sep 2023 • Zizhang Wu, Yuanzhu Gan, Tianhao Xu, Rui Tang, Jian Pu
We aim for accurate and efficient line landmark detection for valet parking, which is a long-standing yet unsolved problem in autonomous driving.
no code implementations • 20 Sep 2023 • Zizhang Wu, Xinyuan Chen, Fan Song, Yuanzhu Gan, Tianhao Xu, Jian Pu, Rui Tang
In this paper, wepresent the Parking Pedestrian Dataset (PPD), a large-scale fisheye dataset to support research dealing with real-world pedestrians, especially with occlusions and diverse postures.
no code implementations • 26 Sep 2023 • Zizhang Wu, Zhuozheng Li, Zhi-Gang Fan, Yunzhe Wu, Xiaoquan Wang, Rui Tang, Jian Pu
Monocular depth estimation is challenging due to its inherent ambiguity and ill-posed nature, yet it is quite important to many applications.
no code implementations • 13 Oct 2023 • Feng Jiang, Chaoping Tu, Gang Zhang, Jun Li, Hanqing Huang, Junyu Lin, Di Feng, Jian Pu
LiDAR and camera are two critical sensors for multi-modal 3D semantic segmentation and are supposed to be fused efficiently and robustly to promise safety in various real-world scenarios.
no code implementations • 5 Mar 2024 • Jiawei Hou, Xiaoyan Li, Wenhao Guan, Gang Zhang, Di Feng, Yuheng Du, xiangyang xue, Jian Pu
In autonomous driving, 3D occupancy prediction outputs voxel-wise status and semantic labels for more comprehensive understandings of 3D scenes compared with traditional perception tasks, such as 3D object detection and bird's-eye view (BEV) semantic segmentation.
1 code implementation • 28 Apr 2023 • Shoumeng Qiu, Feng Jiang, Haiqiang Zhang, xiangyang xue, Jian Pu
In this paper, we propose a novel multi-to-single knowledge distillation framework for the 3D point cloud semantic segmentation task to boost the performance of those hard classes.
1 code implementation • 22 Sep 2023 • Yuxiang Yan, Boda Liu, Jianfei Ai, Qinbu Li, Ru Wan, Jian Pu
To address this, we introduce PointSSC, the first cooperative vehicle-infrastructure point cloud benchmark for semantic scene completion.
1 code implementation • 1 Feb 2022 • Jie Chen, Weiqi Liu, Jian Pu
Based on the homophily assumption, the current message passing always aggregates features of connected nodes, such as the graph Laplacian smoothing process.
1 code implementation • 18 Oct 2022 • Jie Chen, Shouzhen Chen, Mingyuan Bai, Junbin Gao, Junping Zhang, Jian Pu
Then, we introduce a novel structure-mixing knowledge distillation strategy to enhance the learning ability of MLPs for structure information.
1 code implementation • CVPR 2023 • Jie Chen, Zilong Li, Yin Zhu, Junping Zhang, Jian Pu
We design a simple yet effective HopGNN framework that can easily utilize existing GNNs to achieve hop interaction.
1 code implementation • 27 Mar 2021 • Yiqun Liu, Yi Zeng, Jian Pu, Hongming Shan, Peiyang He, Junping Zhang
In this work, we propose a self-supervised gait recognition method, termed SelfGait, which takes advantage of the massive, diverse, unlabeled gait data as a pre-training process to improve the representation abilities of spatiotemporal backbones.
1 code implementation • 19 Mar 2022 • Jie Chen, Shouzhen Chen, Junbin Gao, Zengfeng Huang, Junping Zhang, Jian Pu
Moreover, we propose a simple yet effective Conv-Agnostic GNN framework (CAGNNs) to enhance the performance of most GNNs on heterophily datasets by learning the neighbor effect for each node.
1 code implementation • 22 Apr 2023 • Feng Jiang, Heng Gao, Shoumeng Qiu, Haiqiang Zhang, Ru Wan, Jian Pu
However, it is difficult for existing models to achieve both high inference speed and accuracy simultaneously.
1 code implementation • 25 Feb 2023 • Jiawei Hou, Qi Chen, Yurong Cheng, Guang Chen, xiangyang xue, Taiping Zeng, Jian Pu
However, there is a lack of underground parking scenario datasets with multiple sensors and well-labeled images that support both SLAM tasks and perception tasks, such as semantic segmentation and parking slot detection.