SOTAVerified

Scene Flow Estimation

Optical flow is a two-dimensional motion field in the image plane. It is the projection of the three-dimensional motion of the world. If the world is completely non-rigid, the motions of the points in the scene may all be indepen- dent of each other. One representation of the scene motion is therefore a dense three-dimensional vector field defined for every point on every surface in the scene. By analogy with optical flow, we refer to this three-dimensional motion field as scene flow.

Source: Vedula, Sundar, et al. "Three-dimensional scene flow." IEEE transactions on pattern analysis and machine intelligence 27.3 (2005): 475-480. pdf

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–150 of 152 papers

TitleStatusHype
RCP: Recurrent Closest Point for Scene Flow Estimation on 3D Point Clouds—0
UnPWC-SVDLO: Multi-SVD on PointPWC for Unsupervised Lidar Odometry—0
RAFT-MSF: Self-Supervised Monocular Scene Flow using Recurrent Optimizer—0
RMS-FlowNet: Efficient and Robust Multi-Scale Scene Flow Estimation for Large-Scale Point Clouds—0
Self-Supervised Robust Scene Flow Estimation via the Alignment of Probability Density Functions—0
DetFlowTrack: 3D Multi-object Tracking based on Simultaneous Optimization of Object Detection and Scene Flow Estimation—0
RCP: Recurrent Closest Point for Point CloudCode0
Exploiting Rigidity Constraints for LiDAR Scene Flow Estimation—0
Learning Scene Dynamics from Point Cloud Sequences—0
Attentive and Contrastive Learning for Joint Depth and Motion Field Estimation—0
Residual 3D Scene Flow Learning with Context-Aware Feature Extraction—0
Neural UpFlow: A Scene Flow Learning Approach to Increase the Apparent Resolution of Particle-Based Liquids—0
Self-Point-Flow: Self-Supervised Scene Flow Estimation from Point Clouds with Optimal Transport and Random Walk—0
Occlusion Guided Self-supervised Scene Flow Estimation on 3D Point CloudsCode0
Optical flow and scene flow estimation: A survey—0
Warping of Radar Data into Camera Image for Cross-Modal Supervision in Automotive Applications—0
FlowMOT: 3D Multi-Object Tracking by Scene Flow Association—0
Occlusion Guided Scene Flow Estimation on 3D Point CloudsCode0
FlowStep3D: Model Unrolling for Self-Supervised Scene Flow EstimationCode0
EffiScene: Efficient Per-Pixel Rigidity Inference for Unsupervised Joint Learning of Optical Flow, Depth, Camera Pose and Motion Segmentation—0
Do not trust the neighbors! Adversarial Metric Learning for Self-Supervised Scene Flow Estimation—0
Hierarchical Attention Learning of Scene Flow in 3D Point Clouds—0
DeepLiDARFlow: A Deep Learning Architecture For Scene Flow Estimation Using Monocular Camera and Sparse LiDARCode0
ResFPN: Residual Skip Connections in Multi-Resolution Feature Pyramid Networks for Accurate Dense Pixel Matching—0
Consistency Guided Scene Flow Estimation—0
FlowNet3D++: Geometric Losses For Deep Scene Flow Estimation—0
Just Go with the Flow: Self-Supervised Scene Flow EstimationCode0
LiDAR-Flow: Dense Scene Flow Estimation from Sparse LiDAR and Stereo Images—0
SENSE: a Shared Encoder Network for Scene-flow EstimationCode0
Joint Stereo Video Deblurring, Scene Flow Estimation and Moving Object Segmentation—0
Mono-SF: Multi-View Geometry Meets Single-View Depth for Monocular Scene Flow Estimation of Dynamic Traffic Scenes—0
A Conditional Adversarial Network for Scene Flow EstimationCode0
Deep Rigid Instance Scene Flow—0
Self-Supervised Flow Estimation using Geometric Regularization with Applications to Camera Image and Grid Map Sequences—0
PWOC-3D: Deep Occlusion-Aware End-to-End Scene Flow EstimationCode0
SceneFlowFields++: Multi-frame Matching, Visibility Prediction, and Robust Interpolation for Scene Flow Estimation—0
Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography—0
Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic UnderstandingCode0
Dense Scene Flow from Stereo Disparity and Optical Flow—0
Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow EstimationCode0
SceneEDNet: A Deep Learning Approach for Scene Flow EstimationCode0
Every Pixel Counts: Unsupervised Geometry Learning with Holistic 3D Motion Understanding—0
PointFlowNet: Learning Representations for Rigid Motion Estimation from Point Clouds—0
4D Temporally Coherent Light-field Video—0
Learning Rigidity in Dynamic Scenes with a Moving Camera for 3D Motion Field EstimationCode0
Combining Stereo Disparity and Optical Flow for Basic Scene Flow—0
Multiframe Scene Flow with Piecewise Rigid Motion—0
Bounding Boxes, Segmentations and Object Coordinates: How Important Is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?—0
Simultaneous Stereo Video Deblurring and Scene Flow Estimation—0
Scene Flow Estimation: A Survey—0
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All datasetsArgoverse 2SpringKITTI 2015 Scene Flow TestKITTI 2015 Scene Flow Training

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FastNSFEPE 3-Way0.11—Unverified
2FastFlow3DEPE 3-Way0.06—Unverified
3NSFPEPE 3-Way0.06—Unverified
4ZeroFlow 5x XLEPE 3-Way0.05—Unverified
5SeFlowEPE 3-Way0.05—Unverified
6TrackFlowEPE 3-Way0.05—Unverified
7DeFlowEPE 3-Way0.03—Unverified
#ModelMetricClaimedVerifiedStatus
1CamLiFlow (K)1px total85.31—Unverified
2RAFT-3D (F)1px total78.82—Unverified
3M-FUSE (K)1px total62.49—Unverified
4CamLiFlow (F)1px total50.08—Unverified
5RAFT-3D (K)1px total37.26—Unverified
6M-FUSE (F)1px total34.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Self-Mono-SFSF-all49.54—Unverified
2Multi-Mono-SFSF-all44.04—Unverified
3PWOC-3DSF-all15.69—Unverified
4CamLiRAFTSF-all4.26—Unverified
#ModelMetricClaimedVerifiedStatus
1Self-Mono-SFD1-all31.25—Unverified
2Multi-Mono-SFD1-all27.33—Unverified
3EPCD1-all26.81—Unverified
4EPC++D1-all23.84—Unverified