Real-time sensing and modeling of the human body, especially the hands, is an important
research endeavor for various applicative purposes such as in natural human computer …

This work addresses a novel and challenging problem of estimating the full 3D hand shape
and pose from a single RGB image. Most current methods in 3D hand analysis from …

We propose a method for annotating images of a hand manipulating an object with the 3D
poses of both the hand and the object, together with a dataset created using this method …

The rise of deep learning has brought remarkable progress in estimating hand geometry
from images where the hands are part of the scene. This paper focuses on a new problem …

Abstract 6D object pose estimation is a fundamental problem in computer vision.
Convolutional Neural Networks (CNNs) have recently proven to be capable of predicting …

Event cameras sense per-pixel intensity changes and produce asynchronous event streams
with high dynamic range and less motion blur, showing advantages over the conventional …

6D object pose estimation is a fundamental yet challenging problem in computer vision.
Convolutional Neural Networks (CNNs) have recently proven to be capable of predicting …

Despite recent successes in hand pose estimation, there yet remain challenges on RGB-
based 3D hand pose estimation (HPE) under hand-object interaction (HOI) scenarios where …

Category-level object pose estimation aims to find 6D object poses of previously unseen
object instances from known categories without access to object CAD models. To reduce the …

Many recent 6D pose estimation methods exploited object 3D models to generate synthetic
images for training because labels come for free. However, due to the domain shift of data …