109 citations · 127 across the 11 of their papers we have counts for
12 papers
Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola +3
With the recent surge in popularity of AR/VR applications, realistic and accurate control of 3D full-body avatars has become a highly demanded feature. A particular challenge is th…
Multi-Finger Grasping Like Humans
Yuming Du, Philippe Weinzaepfel, Vincent Lepetit +1
Robots with multi-fingered grippers could perform advanced manipulation tasks for us if we were able to properly specify to them what to do. In this study, we take a step in that d…
A Simple and Powerful Global Optimization for Unsupervised Video Object Segmentation
Georgy Ponimatkin, Nermin Samet, Yang Xiao +3
We propose a simple, yet powerful approach for unsupervised object segmentation in videos. We introduce an objective function whose minimum represents the mask of the main salient…
PIZZA: A Powerful Image-only Zero-Shot Zero-CAD Approach to 6 DoF Tracking
Van Nguyen Nguyen, Yuming Du, Yang Xiao +2
Estimating the relative pose of a new object without prior knowledge is a hard problem, while it is an ability very much needed in robotics and Augmented Reality. We present a meth…
TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut
Yangtao Wang, Xi Shen, Yuan Yuan +5
In this paper, we describe a graph-based algorithm that uses the features obtained by a self-supervised transformer to detect and segment salient objects in images and videos. With…
Back to MLP: A Simple Baseline for Human Motion Prediction
Wen Guo, Yuming Du, Xi Shen +3
This paper tackles the problem of human motion prediction, consisting in forecasting future body poses from historically observed sequences. State-of-the-art approaches provide goo…
UVO Challenge on Video-based Open-World Segmentation 2021: 1st Place Solution
Yuming Du, Wen Guo, Yang Xiao +1
In this report, we introduce our (pretty straightforard) two-step "detect-then-match" video instance segmentation method. The first step performs instance segmentation for each fra…
1st Place Solution for the UVO Challenge on Image-based Open-World Segmentation 2021
Yuming Du, Wen Guo, Yang Xiao +1
We describe our two-stage instance segmentation framework we use to compete in the challenge. The first stage of our framework consists of an object detector, which generates objec…
PoseContrast: Class-Agnostic Object Viewpoint Estimation in the Wild with Pose-Aware Contrastive Learning
Yang Xiao, Yuming Du, Renaud Marlet
Motivated by the need for estimating the 3D pose of arbitrary objects, we consider the challenging problem of class-agnostic object viewpoint estimation from images only, without C…
Learning to Better Segment Objects from Unseen Classes with Unlabeled Videos
Yuming Du, Yang Xiao, Vincent Lepetit
The ability to localize and segment objects from unseen classes would open the door to new applications, such as autonomous object learning in active vision. Nonetheless, improving…
Predicting Sharp and Accurate Occlusion Boundaries in Monocular Depth Estimation Using Displacement Fields
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. This is unfortunat…
Rethinking on Multi-Stage Networks for Human Pose Estimation
Wenbo Li, Zhicheng Wang, Binyi Yin +7
Existing pose estimation approaches fall into two categories: single-stage and multi-stage methods. While multi-stage methods are seemingly more suited for the task, their performa…