ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1909.07031
  4. Cited By
Multi-person Pose Tracking using Sequential Monte Carlo with
  Probabilistic Neural Pose Predictor

Multi-person Pose Tracking using Sequential Monte Carlo with Probabilistic Neural Pose Predictor

16 September 2019
Masashi Okada
Shinji Takenaka
T. Taniguchi
ArXivPDFHTML

Papers citing "Multi-person Pose Tracking using Sequential Monte Carlo with Probabilistic Neural Pose Predictor"

2 / 2 papers shown
Title
DensePose: Dense Human Pose Estimation In The Wild
DensePose: Dense Human Pose Estimation In The Wild
R. Güler
Natalia Neverova
Iasonas Kokkinos
3DH
181
1,386
0
01 Feb 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
1