Add to ORKGInferring 3D human pose from 2D images is a challenging and long-standing problem in the field of computer vision with many applications including motion capture, virtual reality, surveillance or gait analysis for sports and medicine. We present preliminary results for a method to estimate 3D pose from 2D video containing a single person and a static background without the need for any manual landmark annotations. We achieve this by formulating a simple yet effective self-supervision task: our model is required to reconstruct a random frame of a video given a frame from another timepoint and a rendered image of a transformed human shape template. Crucially for optimisation, our ray casting based rendering pipeline is fully differentiable, e...
International audienceThis paper addresses the problem of 3D human pose estimation in the wild. A si...
Abstract: Human pose estimation is a key step to action recognition. We propose a method of estimati...
International audienceIn this work we address the problem of estimating 3D human pose from a single ...
Three-dimensional human pose and shape estimation is an important problem in the computer vision com...
The neural network based approach for 3D human pose estimation from monocular images has attracted g...
Human and non-human pose estimation has been studied within the computer vision community for many d...
Automatic 3D reconstruction of human poses from monocular images is a challenging and popular topic ...
With the success of deep learning in the field of computer vision, most state-of-the-art approaches ...
The rise of deep learning technology has broadly promoted the practical application of artificial in...
Human motion capture either requires multi-camera systems or is unreliable using single-view input d...
We address the problem of 3D human pose estimation from 2D input images using only weakly supervised...
We propose embodied scene-aware human pose estimation where we estimate 3D poses based on a simulate...
The three-dimensional motion of humans is underdetermined when the observation is limited to a singl...
peer reviewedIn this paper, we present a two-step methodology to improve existing human pose estimat...
This thesis proposes, develops and evaluates different convolutional neural network based methods fo...
International audienceThis paper addresses the problem of 3D human pose estimation in the wild. A si...
Abstract: Human pose estimation is a key step to action recognition. We propose a method of estimati...
International audienceIn this work we address the problem of estimating 3D human pose from a single ...
Three-dimensional human pose and shape estimation is an important problem in the computer vision com...
The neural network based approach for 3D human pose estimation from monocular images has attracted g...
Human and non-human pose estimation has been studied within the computer vision community for many d...
Automatic 3D reconstruction of human poses from monocular images is a challenging and popular topic ...
With the success of deep learning in the field of computer vision, most state-of-the-art approaches ...
The rise of deep learning technology has broadly promoted the practical application of artificial in...
Human motion capture either requires multi-camera systems or is unreliable using single-view input d...
We address the problem of 3D human pose estimation from 2D input images using only weakly supervised...
We propose embodied scene-aware human pose estimation where we estimate 3D poses based on a simulate...
The three-dimensional motion of humans is underdetermined when the observation is limited to a singl...
peer reviewedIn this paper, we present a two-step methodology to improve existing human pose estimat...
This thesis proposes, develops and evaluates different convolutional neural network based methods fo...
International audienceThis paper addresses the problem of 3D human pose estimation in the wild. A si...
Abstract: Human pose estimation is a key step to action recognition. We propose a method of estimati...
International audienceIn this work we address the problem of estimating 3D human pose from a single ...