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

Showing 126150 of 152 papers

TitleStatusHype
Deep Rigid Instance Scene Flow0
Self-Supervised Multi-Frame Neural Scene Flow0
Self-Supervised Robust Scene Flow Estimation via the Alignment of Probability Density Functions0
Self-Supervised Scene Flow Estimation with Point-Voxel Fusion and Surface Representation0
Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography0
SemanticFlow: A Self-Supervised Framework for Joint Scene Flow Prediction and Instance Segmentation in Dynamic Environments0
SeMoLi: What Moves Together Belongs Together0
4D Temporally Coherent Light-field Video0
Consistency Guided Scene Flow Estimation0
Simultaneous Stereo Video Deblurring and Scene Flow Estimation0
Combining Stereo Disparity and Optical Flow for Basic Scene Flow0
SSFlowNet: Semi-supervised Scene Flow Estimation On Point Clouds With Pseudo Label0
3D Scene Flow Estimation on Pseudo-LiDAR: Bridging the Gap on Estimating Point Motion0
CMU-Flownet: Exploring Point Cloud Scene Flow Estimation in Occluded Scenario0
TARS: Traffic-Aware Radar Scene Flow Estimation0
Toward Scalable, Flexible Scene Flow for Point Clouds0
Bounding Boxes, Segmentations and Object Coordinates: How Important Is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?0
LiDAR-Flow: Dense Scene Flow Estimation from Sparse LiDAR and Stereo Images0
Learning Scene Dynamics from Point Cloud Sequences0
Layered RGBD Scene Flow Estimation0
Mono-SF: Multi-View Geometry Meets Single-View Depth for Monocular Scene Flow Estimation of Dynamic Traffic Scenes0
MoVieS: Motion-Aware 4D Dynamic View Synthesis in One Second0
Joint Stereo Video Deblurring, Scene Flow Estimation and Moving Object Segmentation0
Multiframe Scene Flow with Piecewise Rigid Motion0
UnPWC-SVDLO: Multi-SVD on PointPWC for Unsupervised Lidar Odometry0
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Benchmark Results

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