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 • 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 • 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 • 15 Aug 2023 • Zizhang Wu, Yuanzhu Gan, Tianhao Xu, Fan Wang
To address this issue, we propose a Graph-Segmenter, including a Graph Transformer and a Boundary-aware Attention module, which is an effective network for simultaneously modeling the more profound relation between windows in a global view and various pixels inside each window as a local one, and for substantial low-cost boundary adjustment.
no code implementations • 15 Aug 2023 • Zizhang Wu, Chenxin Yuan, Hongyang Wei, Fan Song, Tianhao Xu
The compiled dataset consists of 650K images, including different face and vehicle license plate information captured by the surround-view fisheye camera.
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 • 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 • 13 Dec 2022 • Zizhang Wu, Man Wang, Weiwei Sun, Yuchen Li, Tianhao Xu, Fan Wang, Keke Huang
Channel and spatial attention mechanism has proven to provide an evident performance boost of deep convolution neural networks (CNNs).
no code implementations • 8 Dec 2022 • Zizhang Wu, Tianhao Xu, Fan Wang, Xiaoquan Wang, Jing Song
Vehicle re-identification (Re-ID) is a critical component of the autonomous driving perception system, and research in this area has accelerated in recent years.
no code implementations • 8 Dec 2022 • Zizhang Wu, Xinyuan Chen, Jizheng Wang, Xiaoquan Wang, Yuanzhu Gan, Muqing Fang, Tianhao Xu
Obtaining the position of ego-vehicle is a crucial prerequisite for automatic control and path planning in the field of autonomous driving.
no code implementations • 8 Dec 2022 • Zizhang Wu, Yuanzhu Gan, Xianzhi Li, Yunzhe Wu, Xiaoquan Wang, Tianhao Xu, Fan Wang
Most existing networks based on public datasets may generalize suboptimal results on these valet parking scenes, also affected by the fisheye distortion.
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 • 28 Jan 2022 • Zizhang Wu, Jason Wang, Tianhao Xu, Fan Wang
The owner-member relationship between wheels and vehicles contributes significantly to the 3D perception of vehicles, especially in embedded environments.
no code implementations • 14 Dec 2021 • Yongkang Zhang, Jun Li, Guoming Wu, Han Zhang, Zhiping Shi, Zhaoxun Liu, Zizhang Wu, Na Jiang
The temporal sequence self-supervision module we employ unprecedentedly adopts the streamlined strategy of "random batch random channel" to reverse the sequence of video frames, allowing robust extractions of motion information representation from inversed temporal dimensions and improving the generalization capability of the model.
no code implementations • 19 Jul 2021 • Zizhang Wu, Wenkai Zhang, Jizheng Wang, Man Wang, Yuanzhu Gan, Xinchao Gou, Muqing Fang, Jing Song
The 3D visual perception for vehicles with the surround-view fisheye camera system is a critical and challenging task for low-cost urban autonomous driving.
no code implementations • 30 Apr 2021 • Yanan Wu, He Liu, Songhe Feng, Yi Jin, Gengyu Lyu, Zizhang Wu
Multi-Label Image Classification (MLIC) aims to predict a set of labels that present in an image.
no code implementations • 30 Mar 2021 • Zizhang Wu, Man Wang, Jason Wang, Wenkai Zhang, Muqing Fang, Tianhao Xu
It's worth noting that the owner-member relationship between wheels and vehicles has an significant contribution to the 3D perception of vehicles, especially in the embedded environment.
no code implementations • 28 Mar 2021 • Zhengbo Luo, Zitang Sun, Weilian Zhou, Zizhang Wu, Sei-ichiro Kamata
We show that the widely used DNN design strategy, constantly stacking a small design (usually 2-3 layers), could be easily improved, supported by solid theoretical knowledge and with no extra parameters needed.
no code implementations • 30 Jun 2020 • Zizhang Wu, Man Wang, Lingxiao Yin, Weiwei Sun, Jason Wang, Huangbin Wu
The vehicle re-identification (ReID) plays a critical role in the perception system of autonomous driving, which attracts more and more attention in recent years.
no code implementations • 12 May 2020 • Zizhang Wu, Weiwei Sun, Man Wang, Xiaoquan Wang, Lizhu Ding, Fan Wang
\romannumeral2, Expert knowledge for parking slot detection is under-estimated.
3 code implementations • 24 Feb 2020 • Zechen Liu, Zizhang Wu, Roland Tóth
Estimating 3D orientation and translation of objects is essential for infrastructure-less autonomous navigation and driving.
Ranked #23 on Monocular 3D Object Detection on KITTI Cars Moderate