SOTAVerified

Motion Segmentation

Motion Segmentation is an essential task in many applications in Computer Vision and Robotics, such as surveillance, action recognition and scene understanding. The classic way to state the problem is the following: given a set of feature points that are tracked through a sequence of images, the goal is to cluster those trajectories according to the different motions they belong to. It is assumed that the scene contains multiple objects that are moving rigidly and independently in 3D-space.

Source: Robust Motion Segmentation from Pairwise Matches

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 212 papers

TitleStatusHype
Motion Segmentation Using Locally Affine Atom Voting—0
Motion Segmentation via Global and Local Sparse Subspace Optimization—0
Multi-Mutual Consistency Induced Transfer Subspace Learning for Human Motion Segmentation—0
Neuromorphic Vision-based Motion Segmentation with Graph Transformer Neural Network—0
NudgeSeg: Zero-Shot Object Segmentation by Repeated Physical Interaction—0
Object Detection, Tracking, and Motion Segmentation for Object-level Video Segmentation—0
Object Discovery in Videos as Foreground Motion Clustering—0
On Moving Object Segmentation from Monocular Video with Transformers—0
Out of the Room: Generalizing Event-Based Dynamic Motion Segmentation for Complex Scenes—0
PAMOCAT: Automatic retrieval of specified postures—0
Parametric Object Motion from Blur—0
ProgressiveMotionSeg: Mutually Reinforced Framework for Event-Based Motion Segmentation—0
Quantum Motion Segmentation—0
Quickest Moving Object Detection—0
Reconstructing Articulated Rigged Models from RGB-D Videos—0
ReD-SFA: Relation Discovery Based Slow Feature Analysis for Trajectory Clustering—0
Retina-Inspired Object Motion Segmentation for Event-Cameras—0
Rigid Motion Segmentation using Randomized Voting—0
Robust Multi-body Feature Tracker: A Segmentation-free Approach—0
Robust Real-time RGB-D Visual Odometry in Dynamic Environments via Rigid Motion Model—0
Robust Subspace Segmentation with Block-diagonal Prior—0
Robust Video Background Identification by Dominant Rigid Motion Estimation—0
ROML: A Robust Feature Correspondence Approach for Matching Objects in A Set of Images—0
RoMo: Robust Motion Segmentation Improves Structure from Motion—0
Scalable Sparse Subspace Clustering—0
Scene Flow from Point Clouds with or without Learning—0
Segmentation-Free Dynamic Scene Deblurring—0
Segmentation Guided Deep HDR Deghosting—0
Self-Supervised Deep Subspace Clustering with Entropy-norm—0
Self-Supervised Relative Depth Learning for Urban Scene Understanding—0
Self-supervised Sparse to Dense Motion Segmentation—0
Self-supervised Video Object Segmentation by Motion Grouping—0
Motion Segmentation by Exploiting Complementary Geometric ModelsCode0
Extending Layered Models to 3D MotionCode0
Robust Motion Segmentation from Pairwise MatchesCode0
Motion-based Object Segmentation based on Dense RGB-D Scene FlowCode0
Moving Objects Detection with a Moving Camera: A Comprehensive ReviewCode0
Learning Articulated Motions From Visual DemonstrationCode0
KDMOS:Knowledge Distillation for Motion SegmentationCode0
Multi-Class Model Fitting by Energy Minimization and Mode-SeekingCode0
Towards Segmenting Anything That MovesCode0
Nested Grassmannians for Dimensionality Reduction with ApplicationsCode0
Motion Segmentation for Neuromorphic Aerial SurveillanceCode0
Robust Subspace Clustering via Smoothed Rank ApproximationCode0
Robust Subspace Clustering via Tighter Rank ApproximationCode0
Adaptive Low-Rank Kernel Subspace ClusteringCode0
Occlusions, Motion and Depth Boundaries with a Generic Network for Disparity, Optical Flow or Scene Flow EstimationCode0
OmniDet: Surround View Cameras based Multi-task Visual Perception Network for Autonomous DrivingCode0
On Matrix Factorizations in Subspace ClusteringCode0
Shape Interaction Matrix Revisited and Robustified: Efficient Subspace Clustering with Corrupted and Incomplete DataCode0
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All datasetsApolloScapeHopkins155KT3DMoSegMTPV62

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Rule BasedAccuracy90—Unverified
2Rel-Att-GCNAccuracy89—Unverified
3MRGCNAccuracy86—Unverified
4MRGCN-LSTMAccuracy72—Unverified
5St-RNNAccuracy63—Unverified
#ModelMetricClaimedVerifiedStatus
1SSCClassification Error2.18—Unverified
2T-LinkageClassification Error1.97—Unverified
3RSIMClassification Error1.01—Unverified
4MVCClassification Error0.31—Unverified
#ModelMetricClaimedVerifiedStatus
1MultiViewClusteringError7.92—Unverified
#ModelMetricClaimedVerifiedStatus
1MVCClassification Error0.65—Unverified