no code implementations • 22 Dec 2021 • Thomas Lucas, Philippe Weinzaepfel, Gregory Rogez
We propose a method to leverage self-supervised methods that provides training signal in the absence of confident pseudo-labels.
1 code implementation • 17 Dec 2020 • Jens Lundell, Enric Corona, Tran Nguyen Le, Francesco Verdoja, Philippe Weinzaepfel, Gregory Rogez, Francesc Moreno-Noguer, Ville Kyrki
While there exists many methods for manipulating rigid objects with parallel-jaw grippers, grasping with multi-finger robotic hands remains a quite unexplored research topic.
1 code implementation • ICLR 2021 • Pau de Jorge, Amartya Sanyal, Harkirat S. Behl, Philip H. S. Torr, Gregory Rogez, Puneet K. Dokania
Recent studies have shown that skeletonization (pruning parameters) of networks \textit{at initialization} provides all the practical benefits of sparsity both at inference and training time, while only marginally degrading their performance.
no code implementations • ICCV 2019 • Valentin Gabeur, Jean-Sebastien Franco, Xavier Martin, Cordelia Schmid, Gregory Rogez
In this paper, we tackle the problem of 3D human shape estimation from single RGB images.
no code implementations • 1 Mar 2018 • Gregory Rogez, Philippe Weinzaepfel, Cordelia Schmid
We propose an end-to-end architecture for joint 2D and 3D human pose estimation in natural images.
3D Human Pose Estimation
3D Multi-Person Pose Estimation (absolute)
+1
no code implementations • CVPR 2017 • Gregory Rogez, Philippe Weinzaepfel, Cordelia Schmid
We propose an end-to-end architecture for joint 2D and 3D human pose estimation in natural images.
Ranked #4 on
3D Multi-Person Pose Estimation (root-relative)
on MuPoTS-3D
(MPJPE metric)
3D Human Pose Estimation
3D Multi-Person Pose Estimation (absolute)
+3
no code implementations • 31 Mar 2016 • Phuc Xuan Nguyen, Gregory Rogez, Charless Fowlkes, Deva Ramanan
Micro-videos are six-second videos popular on social media networks with several unique properties.
no code implementations • ICCV 2015 • James S. Supancic III, Gregory Rogez, Yi Yang, Jamie Shotton, Deva Ramanan
To spur further progress we introduce a challenging new dataset with diverse, cluttered scenes.
no code implementations • ICCV 2015 • Gregory Rogez, James S. Supancic III, Deva Ramanan
We analyze functional manipulations of handheld objects, formalizing the problem as one of fine-grained grasp classification.
no code implementations • CVPR 2015 • Gregory Rogez, James S. Supancic III, Deva Ramanan
In egocentric views, hands and arms are observable within a well defined volume in front of the camera.
no code implementations • 24 Apr 2015 • James Steven Supancic III, Gregory Rogez, Yi Yang, Jamie Shotton, Deva Ramanan
To spur further progress we introduce a challenging new dataset with diverse, cluttered scenes.
no code implementations • 29 Nov 2014 • Gregory Rogez, James S. Supancic III, Deva Ramanan
We tackle the problem of estimating the 3D pose of an individual's upper limbs (arms+hands) from a chest mounted depth-camera.
no code implementations • 29 Nov 2014 • Gregory Rogez, James S. Supancic III, Maryam Khademi, Jose Maria Martinez Montiel, Deva Ramanan
We focus on the task of everyday hand pose estimation from egocentric viewpoints.