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 101110 of 212 papers

TitleStatusHype
Motion Segmentation using Frequency Domain Transformer NetworksCode1
Automatic Right Ventricle Segmentation using Multi-Label Fusion in Cardiac MRI0
Distilled Semantics for Comprehensive Scene Understanding from VideosCode1
DymSLAM:4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation0
Self-Supervised Joint Encoding of Motion and Appearance for First Person Action Recognition0
Moving Objects Detection with a Moving Camera: A Comprehensive ReviewCode0
Constructing the F-Graph with a Symmetric Constraint for Subspace Clustering0
Temporal Wasserstein non-negative matrix factorization for non-rigid motion segmentation and spatiotemporal deconvolution0
Subspace Clustering with Active Learning0
Stereo-based Multi-motion Visual Odometry for Mobile Robots0
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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