Flot: Scene flow on point clouds guided by optimal transport

G Puy, A Boulch, R Marlet - European conference on computer vision, 2020‏ - Springer
We propose and study a method called FLOT that estimates scene flow on point clouds. We
start the design of FLOT by noticing that scene flow estimation on point clouds reduces to …

Camliflow: bidirectional camera-lidar fusion for joint optical flow and scene flow estimation

H Liu, T Lu, Y Xu, J Liu, W Li… - Proceedings of the IEEE …, 2022‏ - openaccess.thecvf.com
In this paper, we study the problem of jointly estimating the optical flow and scene flow from
synchronized 2D and 3D data. Previous methods either employ a complex pipeline that …

Self-supervised pillar motion learning for autonomous driving

C Luo, X Yang, A Yuille - … of the IEEE/CVF Conference on …, 2021‏ - openaccess.thecvf.com
Autonomous driving can benefit from motion behavior comprehension when interacting with
diverse traffic participants in highly dynamic environments. Recently, there has been a …

Learning optical flow and scene flow with bidirectional camera-lidar fusion

H Liu, T Lu, Y Xu, J Liu, L Wang - IEEE Transactions on Pattern …, 2023‏ - ieeexplore.ieee.org
In this paper, we study the problem of jointly estimating the optical flow and scene flow from
synchronized 2D and 3D data. Previous methods either employ a complex pipeline that …

Self-supervised object motion and depth estimation from video

Q Dai, V Patil, S Hecker, D Dai… - Proceedings of the …, 2020‏ - openaccess.thecvf.com
We present a self-supervised learning framework to estimate the individual object motion
and monocular depth from video. We model the object motion as a 6 degree-of-freedom …

Fgr: Frustum-aware geometric reasoning for weakly supervised 3d vehicle detection

Y Wei, S Su, J Lu, J Zhou - 2021 IEEE International Conference …, 2021‏ - ieeexplore.ieee.org
In this paper, we investigate the problem of weakly supervised 3D vehicle detection.
Conventional methods for 3D object detection usually require vast amounts of manually …

RMS-FlowNet++: Efficient and Robust Multi-scale Scene Flow Estimation for Large-Scale Point Clouds

R Battrawy, R Schuster, D Stricker - International Journal of Computer …, 2024‏ - Springer
The proposed RMS-FlowNet++ is a novel end-to-end learning-based architecture for
accurate and efficient scene flow estimation that can operate on high-density point clouds …

DeepLiDARFlow: A deep learning architecture for scene flow estimation using monocular camera and sparse LiDAR

R Rishav, R Battrawy, R Schuster… - 2020 IEEE/RSJ …, 2020‏ - ieeexplore.ieee.org
Scene flow is the dense 3D reconstruction of motion and geometry of a scene. Most state-of-
the-art methods use a pair of stereo images as input for full scene reconstruction. These …

3-d scene flow estimation on pseudo-lidar: Bridging the gap on estimating point motion

C Jiang, G Wang, Y Miao… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
3-D scene flow characterizes how the points at the current time flow to the next time in the 3-
D Euclidean space, which possesses the capacity to infer autonomously the nonrigid motion …

[HTML][HTML] Object Detection and Information Perception by Fusing YOLO-SCG and Point Cloud Clustering

C Liu, Z Zhao, Y Zhou, L Ma, X Sui, Y Huang, X Yang… - Sensors, 2024‏ - mdpi.com
Robots need to sense information about the external environment before moving, which
helps them to recognize and understand their surroundings so that they can plan safe and …