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

Showing 6170 of 212 papers

TitleStatusHype
Contour Flow: Middle-Level Motion Estimation by Combining Motion Segmentation and Contour Alignment0
Automatic Right Ventricle Segmentation using Multi-Label Fusion in Cardiac MRI0
A New Model and Simple Algorithms for Multi-label Mumford-Shah Problems0
Discovering the Physical Parts of an Articulated Object Class From Multiple Videos0
Clustering with Hypergraphs: The Case for Large Hyperedges0
Differentially private subspace clustering0
DGSAC: Density Guided Sampling and Consensus0
Channel-wise Motion Features for Efficient Motion Segmentation0
A New Approach To Two-View Motion Segmentation Using Global Dimension Minimization0
Act the Part: Learning Interaction Strategies for Articulated Object Part Discovery0
Show:102550
← PrevPage 7 of 22Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Rule BasedAccuracy90Unverified
2Rel-Att-GCNAccuracy89Unverified
3MRGCNAccuracy86Unverified
4MRGCN-LSTMAccuracy72Unverified
5St-RNNAccuracy63Unverified
#ModelMetricClaimedVerifiedStatus
1SSCClassification Error2.18Unverified
2T-LinkageClassification Error1.97Unverified
3RSIMClassification Error1.01Unverified
4MVCClassification Error0.31Unverified
#ModelMetricClaimedVerifiedStatus
1MultiViewClusteringError7.92Unverified
#ModelMetricClaimedVerifiedStatus
1MVCClassification Error0.65Unverified