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 101–125 of 212 papers

TitleStatusHype
Monocular Instance Motion Segmentation for Autonomous Driving: KITTI InstanceMotSeg Dataset and Multi-task Baseline—0
Jointly learning visual motion and confidence from local patches in event cameras—0
On the Usage of the Trifocal Tensor in Motion SegmentationCode0
DGSAC: Density Guided Sampling and Consensus—0
Multi-Mutual Consistency Induced Transfer Subspace Learning for Human Motion Segmentation—0
Learning Visual Motion Segmentation Using Event Surfaces—0
Is an Affine Constraint Needed for Affine Subspace Clustering?—0
Automatic Right Ventricle Segmentation using Multi-Label Fusion in Cardiac MRI—0
DymSLAM:4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation—0
Self-Supervised Joint Encoding of Motion and Appearance for First Person Action Recognition—0
Moving Objects Detection with a Moving Camera: A Comprehensive ReviewCode0
Constructing the F-Graph with a Symmetric Constraint for Subspace Clustering—0
Temporal Wasserstein non-negative matrix factorization for non-rigid motion segmentation and spatiotemporal deconvolution—0
Subspace Clustering with Active Learning—0
Stereo-based Multi-motion Visual Odometry for Mobile Robots—0
Learning event representations for temporal segmentation of image sequences by dynamic graph embedding—0
EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion SaliencyCode0
3D Rigid Motion Segmentation with Mixed and Unknown Number of Models—0
Robust Real-time RGB-D Visual Odometry in Dynamic Environments via Rigid Motion Model—0
Motion Segmentation Using Locally Affine Atom Voting—0
Robust Motion Segmentation from Pairwise MatchesCode0
EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras—0
Robust Video Background Identification by Dominant Rigid Motion Estimation—0
Fine-Grained Semantic Segmentation of Motion Capture Data using Dilated Temporal Fully-Convolutional Networks—0
Towards Segmenting Anything That MovesCode0
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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