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 201212 of 212 papers

TitleStatusHype
Improving Streaming Video Segmentation with Early and Mid-Level Visual Processing0
Context-Aware Modeling and Recognition of Activities in Video0
Scalable Sparse Subspace Clustering0
Fast Rigid Motion Segmentation via Incrementally-Complex Local Models0
A New Model and Simple Algorithms for Multi-label Mumford-Shah Problems0
Large Displacement Optical Flow from Nearest Neighbor Fields0
Distributed Low-rank Subspace Segmentation0
A New Approach To Two-View Motion Segmentation Using Global Dimension Minimization0
Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering0
PAMOCAT: Automatic retrieval of specified postures0
Convex Relaxation of Mixture Regression with Efficient Algorithms0
The Ordered Residual Kernel for Robust Motion Subspace Clustering0
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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