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Flot: Scene flow on point clouds guided by optimal transport
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 …
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
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 …
synchronized 2D and 3D data. Previous methods either employ a complex pipeline that …
Self-supervised pillar motion learning for autonomous driving
Autonomous driving can benefit from motion behavior comprehension when interacting with
diverse traffic participants in highly dynamic environments. Recently, there has been a …
diverse traffic participants in highly dynamic environments. Recently, there has been a …
Learning optical flow and scene flow with bidirectional camera-lidar fusion
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 …
synchronized 2D and 3D data. Previous methods either employ a complex pipeline that …
Self-supervised object motion and depth estimation from video
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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
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 …
helps them to recognize and understand their surroundings so that they can plan safe and …