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 161170 of 212 papers

TitleStatusHype
Attentive and Contrastive Learning for Joint Depth and Motion Field Estimation0
A Unified Model Selection Technique for Spectral Clustering Based Motion Segmentation0
Automatic Right Ventricle Segmentation using Multi-Label Fusion in Cardiac MRI0
Betrayed by Motion: Camouflaged Object Discovery via Motion Segmentation0
BEV-MODNet: Monocular Camera based Bird's Eye View Moving Object Detection for Autonomous Driving0
BEVMOSNet: Multimodal Fusion for BEV Moving Object Segmentation0
Channel-wise Motion Features for Efficient Motion Segmentation0
Clustering with Hypergraphs: The Case for Large Hyperedges0
Coarse-to-Fine Segmentation With Shape-Tailored Scale Spaces0
Coarse-To-Fine Segmentation With Shape-Tailored Continuum Scale Spaces0
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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