292 citations · 727 across the 33 of their papers we have counts for
6 papers · 1 filter
SMPLy Benchmarking 3D Human Pose Estimation in the Wild
Vincent Leroy, Philippe Weinzaepfel, Romain Brégier +2
Predicting 3D human pose from images has seen great recent improvements. Novel approaches that can even predict both pose and shape from a single input image have been introduced,…
Multi-FinGAN: Generative Coarse-To-Fine Sampling of Multi-Finger Grasps
Jens Lundell, Enric Corona, Tran Nguyen Le +5
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. Reaso…
Continual Adaptation of Visual Representations via Domain Randomization and Meta-learning
Riccardo Volpi, Diane Larlus, Grégory Rogez
Most standard learning approaches lead to fragile models which are prone to drift when sequentially trained on samples of a different nature - the well-known "catastrophic forgetti…
DOPE: Distillation Of Part Experts for whole-body 3D pose estimation in the wild
Philippe Weinzaepfel, Romain Brégier, Hadrien Combaluzier +2
We introduce DOPE, the first method to detect and estimate whole-body 3D human poses, including bodies, hands and faces, in the wild. Achieving this level of details is key for a n…
Progressive Skeletonization: Trimming more fat from a network at initialization
Pau de Jorge, Amartya Sanyal, Harkirat S. Behl +3
Recent studies have shown that skeletonization (pruning parameters) of networks \textit{at initialization} provides all the practical benefits of sparsity both at inference and tra…
Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction
Anil Armagan, Guillermo Garcia-Hernando, Seungryul Baek +32
We study how well different types of approaches generalise in the task of 3D hand pose estimation under single hand scenarios and hand-object interaction. We show that the accuracy…