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
Human Pose Estimation Based on Multi-resolution Feature Fusion Network
Weibai Duan,Qishen Li,Sihao Yuan,Xiao Yu +3 more
- 12 Mar 2021
TL;DR: Wang et al. as discussed by the authors fused spatial and semantic information on multiple scale feature maps, in addition, their network use the multi-receptive field fusion module on the same scale features to enhance feature extraction.
Smart design of customized hip prostheses in additive manufacturing by combining numerical and experimental methodologies
Dario Milone,Cristiano De Marchis,Ferruccio Longo,Giorgio Merlino,L. D'Agati,Daniele Catelani,Giacomo Risitano +6 more
- 01 Feb 2023
TL;DR: In this article , the authors developed an algorithm that optimizes hip replacement mechanically using a machine learning algorithm coupled with multi-body and finite element model simulations to accurately evaluate the distribution of the load on the prosthesis.
Multi-View Human Tracking and 3D Localization in Retail
Akash Jadhav
- 23 Jul 2022
TL;DR: The key idea is to use a hierarchical association model for tracking, which uses each human's clothing features, human pose orientation, and relative depth of joints, and runs at over 23fps.
Reward contingency gates selective cholinergic suppression of amygdala neurons
Eyal Y. Kimchi,Anthony Burgos-Robles,Gillian A. Matthews,Tatenda Chakoma,Makenzie Patarino,Javier C. Weddington,Cody A. Siciliano,Wannan Yang,Shaun Foutch,Renee Simons,Ming-fai Fong,Miao Jing,Yulong Li,Daniel B. Polley,Kay M. Tye +14 more
TL;DR: Cholinergic effects are modulated by reward contingency in a target-specific manner to promote conditioned responding and constrain clinical goals of augmenting cholinergic function to improve neuropsychiatric symptoms.
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Pixel-Level Dense Prediction without Decoder
TL;DR: This work proposes a fully decoding-free pixel-level dense prediction network called FlatteNet, in which the high dimensional tensor outputted by the backbone network is directly flattened to fit the desired output resolution.
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