Proceedings ArticleDOI
Joint Graph Decomposition & Node Labeling: Problem, Algorithms, Applications
Evgeny Levinkov,Jonas Uhrig,Siyu Tang,Mohamed Omran,Eldar Insafutdinov,Alexander Kirillov,Carsten Rother,Thomas Brox,Bernt Schiele,Bjoern Andres +9 more
- pp 1904-1912
TLDR
A combinatorial optimization problem whose feasible solutions define both a decomposition and a node labeling of a given graph, which offers a common mathematical abstraction of seemingly unrelated computer vision tasks, including instance-separating semantic segmentation, articulated human body pose estimation and multiple object tracking.Abstract:
We state a combinatorial optimization problem whose feasible solutions define both a decomposition and a node labeling of a given graph. This problem offers a common mathematical abstraction of seemingly unrelated computer vision tasks, including instance-separating semantic segmentation, articulated human body pose estimation and multiple object tracking. Conceptually, it generalizes the unconstrained integer quadratic program and the minimum cost lifted multicut problem, both of which are NP-hard. In order to find feasible solutions efficiently, we define two local search algorithms that converge monotonously to a local optimum, offering a feasible solution at any time. To demonstrate the effectiveness of these algorithms in tackling computer vision tasks, we apply them to instances of the problem that we construct from published data, using published algorithms. We report state-of-the-art application-specific accuracy in the three above-mentioned applications.read more
Citations
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Journal ArticleDOI
OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields
TL;DR: OpenPose as mentioned in this paper uses Part Affinity Fields (PAFs) to learn to associate body parts with individuals in the image, which achieves high accuracy and real-time performance.
Proceedings ArticleDOI
RMPE: Regional Multi-person Pose Estimation
TL;DR: In this paper, a regional multi-person pose estimation (RMPE) framework is proposed to facilitate pose estimation in the presence of inaccurate human bounding boxes, which achieves state-of-the-art performance on the MPII dataset.
Posted Content
OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
TL;DR: OpenPose is released, the first open-source realtime system for multi-person 2D pose detection, including body, foot, hand, and facial keypoints, and the first combined body and foot keypoint detector, based on an internal annotated foot dataset.
Book ChapterDOI
Recovering Accurate {3D} Human Pose in the Wild Using {IMUs} and a Moving Camera
TL;DR: This work proposes a method that combines a single hand-held camera and a set of Inertial Measurement Units (IMUs) attached at the body limbs to estimate accurate 3D poses in the wild and obtains an accuracy of 26 mm, which makes it accurate enough to serve as a benchmark for image-based 3D pose estimation in theWild.
Book ChapterDOI
PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model
TL;DR: In this article, a CNN is used to detect individual keypoints and predict their relative displacements, allowing them to group keypoints into person pose instances and then associate semantic person pixels with their corresponding person instance, delivering instance-level person segmentations.
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