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 91100 of 212 papers

TitleStatusHype
Joint SFM and Detection Cues for Monocular 3D Localization in Road Scenes0
Divided Attention: Unsupervised Multi-Object Discovery with Contextually Separated Slots0
Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices0
Large Displacement Optical Flow from Nearest Neighbor Fields0
Layered Motion Fusion: Lifting Motion Segmentation to 3D in Egocentric Videos0
Learned Trajectory Embedding for Subspace Clustering0
Dynamic Point Maps: A Versatile Representation for Dynamic 3D Reconstruction0
Learning event representations for temporal segmentation of image sequences by dynamic graph embedding0
Learning Motion Patterns in Videos0
BEVMOSNet: Multimodal Fusion for BEV Moving Object 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