1 code implementation • 4 Feb 2024 • Lu Zhang, Peiliang Li, Sikang Liu, Shaojie Shen
This paper presents a Simple and effIcient Motion Prediction baseLine (SIMPL) for autonomous vehicles.
no code implementations • 3 Mar 2023 • Jieqi Shi, Peiliang Li, Xiaozhi Chen, Shaojie Shen
In this paper, we propose a quality evaluation network to score the point clouds and help judge the quality of the point cloud before applying the completion model.
no code implementations • 17 Nov 2022 • Jieqi Shi, Peiliang Li, Xiaozhi Chen, Shaojie Shen
The image-based 3D object detection task expects that the predicted 3D bounding box has a ``tightness'' projection (also referred to as cuboid), which fits the object contour well on the image while still keeping the geometric attribute on the 3D space, e. g., physical dimension, pairwise orthogonal, etc.
1 code implementation • CVPR 2022 • Qing Lian, Peiliang Li, Xiaozhi Chen
Based on the object depth, the dense coordinates patch together with the corresponding object features is reprojected to the image space to build a cost volume in a joint semantic and geometric error manner.
no code implementations • 7 Feb 2022 • Jieqi Shi, Lingyun Xu, Peiliang Li, Xiaozhi Chen, Shaojie Shen
With the help of gated recovery units(GRU) and attention mechanisms as temporal units, we propose a point cloud completion framework that accepts a sequence of unaligned and sparse inputs, and outputs consistent and aligned point clouds.
1 code implementation • 2 Nov 2021 • Lu Zhang, Peiliang Li, Jing Chen, Shaojie Shen
In this paper, we present a graph-based trajectory prediction network named the Dual Scale Predictor (DSP), which encodes both the static and dynamical driving context in a hierarchical manner.
no code implementations • 20 Oct 2020 • Jieqi Shi, Peiliang Li, Shaojie Shen
A robust 3D object tracker which continuously tracks surrounding objects and estimates their trajectories is key for self-driving vehicles.
no code implementations • CVPR 2020 • Peiliang Li, Jieqi Shi, Shaojie Shen
Directly learning multiple 3D objects motion from sequential images is difficult, while the geometric bundle adjustment lacks the ability to localize the invisible object centroid.
no code implementations • 11 Sep 2019 • Peiliang Li, Si-Qi Liu, Shaojie Shen
We propose a 3D object detection system with multi-sensor refinement in the context of autonomous driving.
4 code implementations • CVPR 2019 • Peiliang Li, Xiaozhi Chen, Shaojie Shen
Our method, called Stereo R-CNN, extends Faster R-CNN for stereo inputs to simultaneously detect and associate object in left and right images.
3D Object Detection From Stereo Images Autonomous Driving +3
no code implementations • ECCV 2018 • Peiliang Li, Tong Qin, Shaojie Shen
We propose a stereo vision-based approach for tracking the camera ego-motion and 3D semantic objects in dynamic autonomous driving scenarios.
11 code implementations • 13 Aug 2017 • Tong Qin, Peiliang Li, Shaojie Shen
A monocular visual-inertial system (VINS), consisting of a camera and a low-cost inertial measurement unit (IMU), forms the minimum sensor suite for metric six degrees-of-freedom (DOF) state estimation.
Robotics