Papers Self-supervised Scene Flow Estimation
“Self-supervised Scene Flow Estimation” 태그가 달린 논문 21편 · 필터 해제
Motion Cues from Image-based Point Tracking for LiDAR Scene Flow Estimation
LiDAR scene flow estimation is essential for autonomous driving, as it provides 3D motion for each point. Self-supervised approaches use static-dynamic classification to mitigate the imbalance between static and dynamic …
Self-supervised Scene Flow EstimationAutonomous DrivingPoint TrackingVoteFlow: Enforcing Local Rigidity in Self-Supervised Scene Flow
Scene flow estimation aims to recover per-point motion from two adjacent LiDAR scans. However, in real-world applications such as autonomous driving, points rarely move independently of others, especially for nearby poin…
Autonomous DrivingComputational EfficiencyInductive BiasScene Flow Estimation+1Self-Supervised Scene Flow Estimation with Point-Voxel Fusion and Surface Representation
Scene flow estimation aims to generate the 3D motion field of points between two consecutive frames of point clouds, which has wide applications in various fields. Existing point-based methods ignore the irregularity of …
Scene Flow EstimationSelf-supervised Scene Flow EstimationSeFlow: A Self-Supervised Scene Flow Method in Autonomous Driving
Scene flow estimation predicts the 3D motion at each point in successive LiDAR scans. This detailed, point-level, information can help autonomous vehicles to accurately predict and understand dynamic changes in their sur…
Autonomous DrivingAutonomous VehiclesObjectScene Flow Estimation+1ICP-Flow: LiDAR Scene Flow Estimation with ICP
Scene flow characterizes the 3D motion between two LiDAR scans captured by an autonomous vehicle at nearby timesteps. Prevalent methods consider scene flow as point-wise unconstrained flow vectors that can be learned by …
Autonomous DrivingScene Flow EstimationSelf-supervised Scene Flow EstimationFedRSU: Federated Learning for Scene Flow Estimation on Roadside Units
Roadside unit (RSU) can significantly improve the safety and robustness of autonomous vehicles through Vehicle-to-Everything (V2X) communication. Currently, the usage of a single RSU mainly focuses on real-time inference…
Autonomous VehiclesFederated LearningScene Flow EstimationSelf-Supervised Learning+1OptFlow: Fast Optimization-based Scene Flow Estimation without Supervision
Scene flow estimation is a crucial component in the development of autonomous driving and 3D robotics, providing valuable information for environment perception and navigation. Despite the advantages of learning-based sc…
Autonomous DrivingPoint Cloud RegistrationScene Flow EstimationSelf-supervised Scene Flow Estimation+1ZeroFlow: Scalable Scene Flow via Distillation
Scene flow estimation is the task of describing the 3D motion field between temporally successive point clouds. State-of-the-art methods use strong priors and test-time optimization techniques, but require on the order o…
Scene Flow EstimationSelf-supervised Scene Flow EstimationFast Neural Scene Flow
Neural Scene Flow Prior (NSFP) is of significant interest to the vision community due to its inherent robustness to out-of-distribution (OOD) effects and its ability to deal with dense lidar points. The approach utilizes…
Autonomous DrivingScene Flow EstimationSelf-supervised Scene Flow Estimation3D Object Detection with a Self-supervised Lidar Scene Flow Backbone
State-of-the-art lidar-based 3D object detection methods rely on supervised learning and large labeled datasets. However, annotating lidar data is resource-consuming, and depending only on supervised learning limits the …
3D Object DetectionObjectobject-detectionObject Detection+3Self-Supervised Robust Scene Flow Estimation via the Alignment of Probability Density Functions
In this paper, we present a new self-supervised scene flow estimation approach for a pair of consecutive point clouds. The key idea of our approach is to represent discrete point clouds as continuous probability density …
Scene Flow EstimationSelf-Supervised LearningSelf-supervised Scene Flow EstimationSelf-Supervised Scene Flow Estimation with 4-D Automotive Radar
Scene flow allows autonomous vehicles to reason about the arbitrary motion of multiple independent objects which is the key to long-term mobile autonomy. While estimating the scene flow from LiDAR has progressed recently…
Autonomous VehiclesMotion SegmentationScene Flow EstimationSelf-Supervised Learning+1Neural Scene Flow Prior
Before the deep learning revolution, many perception algorithms were based on runtime optimization in conjunction with a strong prior/regularization penalty. A prime example of this in computer vision is optical and scen…
Autonomous DrivingScene Flow EstimationSelf-supervised Scene Flow EstimationSelf-Point-Flow: Self-Supervised Scene Flow Estimation from Point Clouds with Optimal Transport and Random Walk
Due to the scarcity of annotated scene flow data, self-supervised scene flow learning in point clouds has attracted increasing attention. In the self-supervised manner, establishing correspondences between two point clou…
Scene Flow EstimationSelf-Supervised LearningSelf-supervised Scene Flow EstimationOcclusion Guided Self-supervised Scene Flow Estimation on 3D Point Clouds
Understanding the flow in 3D space of sparsely sampled points between two consecutive time frames is the core stone of modern geometric-driven systems such as VR/AR, Robotics, and Autonomous driving. The lack of real, no…
Autonomous DrivingScene Flow EstimationSelf-supervised Scene Flow EstimationFlowStep3D: Model Unrolling for Self-Supervised Scene Flow Estimation
Estimating the 3D motion of points in a scene, known as scene flow, is a core problem in computer vision. Traditional learning-based methods designed to learn end-to-end 3D flow often suffer from poor generalization. Her…
AllRolling Shutter CorrectionScene Flow EstimationSelf-supervised Scene Flow EstimationAdversarial Self-Supervised Scene Flow Estimation
This work proposes a metric learning approach for self-supervised scene flow estimation. Scene flow estimation is the task of estimating 3D flow vectors for consecutive 3D point clouds. Such flow vectors are fruitful, \e…
Metric LearningScene Flow EstimationSelf-supervised Scene Flow EstimationTripletDo not trust the neighbors! Adversarial Metric Learning for Self-Supervised Scene Flow Estimation
Scene flow is the task of estimating 3D motion vectors to individual points of a dynamic 3D scene. Motion vectors have shown to be beneficial for downstream tasks such as action classification and collision avoidance. Ho…
Action ClassificationCollision AvoidanceMetric LearningScene Flow Estimation+2PointPWC-Net: Cost Volume on Point Clouds for (Self-)Supervised Scene Flow Estimation
We propose a novel end-to-end deep scene flow model, called PointPWC-Net, that directly processes 3D point cloud scenes with large motions in a coarse-to-fine fashion. Flow computed at the coarse level is upsampled and w…
Scene Flow EstimationSelf-supervised Scene Flow EstimationJust Go with the Flow: Self-Supervised Scene Flow Estimation
When interacting with highly dynamic environments, scene flow allows autonomous systems to reason about the non-rigid motion of multiple independent objects. This is of particular interest in the field of autonomous driv…
Autonomous DrivingScene Flow EstimationSelf-supervised Scene Flow Estimation