Open AccessPosted Content
DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model
Eldar Insafutdinov,Leonid Pishchulin,Bjoern Andres,Mykhaylo Andriluka,Mykhaylo Andriluka,Bernt Schiele +5 more
TL;DR: In this paper, an incremental optimization strategy was proposed to explore the search space more efficiently, leading both to better performance and significant speed-up factors for multi-person pose estimation.
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Abstract: The goal of this paper is to advance the state-of-the-art of articulated pose estimation in scenes with multiple people. To that end we contribute on three fronts. We propose (1) improved body part detectors that generate effective bottom-up proposals for body parts; (2) novel image-conditioned pairwise terms that allow to assemble the proposals into a variable number of consistent body part configurations; and (3) an incremental optimization strategy that explores the search space more efficiently thus leading both to better performance and significant speed-up factors. Evaluation is done on two single-person and two multi-person pose estimation benchmarks. The proposed approach significantly outperforms best known multi-person pose estimation results while demonstrating competitive performance on the task of single person pose estimation. Models and code available at this http URL
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Citations
Structural projection points estimation and context priors for oil tank storage estimation in SAR image
TL;DR: Wang et al. as mentioned in this paper modeled the structural projection points description operator to estimate the fine 3D structural parameters of oil tank and invert the storage information, and proposed the SAR image context prior to extract the 3D information of the oil tank targets.
1
Pose estimation of sow and piglets during free farrowing using deep learning
Fahimeh Farahnakian,Farshad Farahnakian,Stefan Björkman,Victor Bloch,Matti Pastell,Jukka Heikkonen +5 more
TL;DR: This study applies deep learning methods to estimate sow and piglet poses in real-time, using a commercial farm's farrowing data to train and validate five architectures, with MobileNet achieving a median test error of 0.61 pixels for sow body part detection.
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A Deep Learning Model for Markerless Pose Estimation Based on Keypoint Augmentation: What Factors Influence Errors in Biomechanical Applications?
Ana V. Ruescas-Nicolau,Enrique Medina-Ripoll,Helios de Rosario,Joaquín Sanchiz Navarro,Eduardo Parrilla,María Carmen Juan Lizandra +5 more
- 17 Mar 2024
TL;DR: A deep learning model for markerless pose estimation based on keypoint augmentation can achieve comparable accuracy to marker-based photogrammetry. Errors in anatomical landmark positions and joint angles are influenced by anatomical landmarks, movement, model, and rotation axis.
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High frequency alternating current neurostimulation decreases nocifensive behavior in a disc herniation model of lumbar radiculopathy
TL;DR: KHFAC stimulation of the sciatic nerve decreased behavioral evidence of pain and disability and supports the idea that KHFAC stimulation applied to a peripheral nerve may be able to treat chronic pain resulting from sciatic nerve root inflammation.
1
•Posted Content
Efficient Pose and Cell Segmentation using Column Generation.
TL;DR: A generic relaxation scheme for solving combinatorial problems using a column generation formulation where the program for generating a column is solved via exact optimization of very small scale integer programs, which results in efficient exploration of the spaces of poses and cells.
1
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Going deeper with convolutions
Christian Szegedy,Wei Liu,Yangqing Jia,Pierre Sermanet,Scott Reed,Dragomir Anguelov,Dumitru Erhan,Vincent Vanhoucke,Andrew Rabinovich +8 more
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