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 151160 of 212 papers

TitleStatusHype
Zero-Shot Monocular Motion Segmentation in the Wild by Combining Deep Learning with Geometric Motion Model Fusion0
Achieving stable subspace clustering by post-processing generic clustering results0
A Continuous Occlusion Model for Road Scene Understanding0
A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models0
Act the Part: Learning Interaction Strategies for Articulated Object Part Discovery0
A Detailed Rubric for Motion Segmentation0
A Multi-cut Formulation for Joint Segmentation and Tracking of Multiple Objects0
A New Approach To Two-View Motion Segmentation Using Global Dimension Minimization0
A New Model and Simple Algorithms for Multi-label Mumford-Shah Problems0
Appearance-Based Refinement for Object-Centric Motion Segmentation0
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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