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Motion Segmentation

13 papers with code · Computer Vision

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

Benchmarks

Greatest papers with code

Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation

CVPR 2019 anuragranj/cc

We address the unsupervised learning of several interconnected problems in low-level vision: single view depth prediction, camera motion estimation, optical flow, and segmentation of a video into the static scene and moving regions.

MONOCULAR DEPTH ESTIMATION MOTION ESTIMATION MOTION SEGMENTATION OPTICAL FLOW ESTIMATION

FlowNet3D: Learning Scene Flow in 3D Point Clouds

CVPR 2019 xingyul/flownet3d

In this work, we propose a novel deep neural network named $FlowNet3D$ that learns scene flow from point clouds in an end-to-end fashion.

MOTION SEGMENTATION

Sparse Subspace Clustering: Algorithm, Theory, and Applications

5 Mar 2012panji1990/Deep-subspace-clustering-networks

In this paper, we propose and study an algorithm, called Sparse Subspace Clustering (SSC), to cluster data points that lie in a union of low-dimensional subspaces.

FACE CLUSTERING MOTION SEGMENTATION

UnOS: Unified Unsupervised Optical-Flow and Stereo-Depth Estimation by Watching Videos

CVPR 2019 baidu-research/UnDepthflow

In this paper, we propose UnOS, an unified system for unsupervised optical flow and stereo depth estimation using convolutional neural network (CNN) by taking advantages of their inherent geometrical consistency based on the rigid-scene assumption.

MOTION SEGMENTATION OPTICAL FLOW ESTIMATION STEREO DEPTH ESTIMATION VISUAL ODOMETRY

Progressive-X: Efficient, Anytime, Multi-Model Fitting Algorithm

ICCV 2019 danini/progressive-x

The Progressive-X algorithm, Prog-X in short, is proposed for geometric multi-model fitting.

MOTION SEGMENTATION

Motion-based Object Segmentation based on Dense RGB-D Scene Flow

14 Apr 2018stanford-iprl-lab/sceneflownet

Our model jointly estimates (i) the segmentation of the scene into an unknown but finite number of objects, (ii) the motion trajectories of these objects and (iii) the object scene flow.

MOTION SEGMENTATION SEMANTIC SEGMENTATION

EpO-Net: Exploiting Geometric Constraints on Dense Trajectories for Motion Saliency

29 Sep 2019mfaisal59/EpONet

To handle the nonrigid background like a sea, we also propose a robust fusion mechanism between motion and appearance-based features.

MOTION SEGMENTATION OPTICAL FLOW ESTIMATION UNSUPERVISED VIDEO OBJECT SEGMENTATION

Adaptive Low-Rank Kernel Subspace Clustering

17 Jul 2017panji1990/Low-rank-kernel-subspace-clustering

In this paper, we present a kernel subspace clustering method that can handle non-linear models.

IMAGE CLUSTERING MOTION SEGMENTATION

Robust Subspace Clustering via Tighter Rank Approximation

30 Oct 2015sckangz/arctangent

For this nonconvex minimization problem, we develop an effective optimization procedure based on a type of augmented Lagrange multipliers (ALM) method.

FACE CLUSTERING MOTION SEGMENTATION