1 code implementation • CVPR 2023 • Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
A particular challenge is that only a sparse tracking signal is available from standalone HMDs (Head Mounted Devices), often limited to tracking the user's head and wrists.
1 code implementation • 19 Sep 2022 • Georgy Ponimatkin, Nermin Samet, Yang Xiao, Yuming Du, Renaud Marlet, Vincent Lepetit
We propose a simple, yet powerful approach for unsupervised object segmentation in videos.
Ranked #1 on Unsupervised Video Object Segmentation on SegTrack v2 (Jaccard (Mean) metric)
1 code implementation • 15 Sep 2022 • Van Nguyen Nguyen, Yuming Du, Yang Xiao, Michael Ramamonjisoa, Vincent Lepetit
Our results on challenging datasets are on par with previous works that require much more information (training images of the target objects, 3D models, and/or depth data).
no code implementations • 1 Sep 2022 • Yangtao Wang, Xi Shen, Yuan Yuan, Yuming Du, Maomao Li, Shell Xu Hu, James L Crowley, Dominique Vaufreydaz
This method also achieves competitive results for unsupervised video object segmentation tasks with the DAVIS, SegTV2, and FBMS datasets.
Ranked #4 on Unsupervised Instance Segmentation on COCO val2017
1 code implementation • 4 Jul 2022 • Wen Guo, Yuming Du, Xi Shen, Vincent Lepetit, Xavier Alameda-Pineda, Francesc Moreno-Noguer
This paper tackles the problem of human motion prediction, consisting in forecasting future body poses from historically observed sequences.
2 code implementations • 22 Oct 2021 • Yuming Du, Wen Guo, Yang Xiao, Vincent Lepetit
In this report, we introduce our (pretty straightforard) two-step "detect-then-match" video instance segmentation method.
1 code implementation • 19 Oct 2021 • Yuming Du, Wen Guo, Yang Xiao, Vincent Lepetit
We describe our two-stage instance segmentation framework we use to compete in the challenge.
1 code implementation • 12 May 2021 • Yang Xiao, Yuming Du, Renaud Marlet
We experimented on Pascal3D+, ObjectNet3D and Pix3D in a cross-dataset fashion, with both seen and unseen classes.
no code implementations • ICCV 2021 • Yuming Du, Yang Xiao, Vincent Lepetit
Through extensive experiments, we show that our method can generate a high-quality training set which significantly boosts the performance of segmenting objects of unseen classes.
2 code implementations • CVPR 2020 • Michael Ramamonjisoa, Yuming Du, Vincent Lepetit
Current methods for depth map prediction from monocular images tend to predict smooth, poorly localized contours for the occlusion boundaries in the input image.
7 code implementations • 1 Jan 2019 • Wenbo Li, Zhicheng Wang, Binyi Yin, Qixiang Peng, Yuming Du, Tianzi Xiao, Gang Yu, Hongtao Lu, Yichen Wei, Jian Sun
Existing pose estimation approaches fall into two categories: single-stage and multi-stage methods.
Ranked #1 on Pose Estimation on COCO minival