Personne
Bugra Tekin
Cette personne n’est plus à l’EPFL
Publications associées (13)
Learning to Align Sequential Actions in the Wild
Pascal Fua, Bugra Tekin, Weizhe Liu
State-of-the-art methods for self-supervised sequential action alignment rely on deep networks that find correspon- dences across videos in time. They either learn frame-to- frame mapping across sequences, which does not leverage temporal information, or a ...
IEEE2022Learning Robust Features and Latent Representations for Single View 3D Pose Estimation of Humans and Objects
Estimating the 3D poses of rigid and articulated bodies is one of the fundamental problems of Computer Vision. It has a broad range of applications including augmented reality, surveillance, animation and human-computer interaction. Despite the ever-growin ...
EPFL2018Learning Latent Representations of 3D Human Pose with Deep Neural Networks
Pascal Fua, Mathieu Salzmann, Vincent Lepetit, Bugra Tekin
Most recent approaches to monocular 3D pose estimation rely on Deep Learning. They either train a Convolutional Neural Network to directly regress from an image to a 3D pose, which ignores the dependencies between human joints, or model these dependencies ...
2018Real-Time Seamless Single Shot 6D Object Pose Prediction
Pascal Fua, Bugra Tekin, Sudipta Sinha
We propose a single-shot approach for simultaneously detecting an object in an RGB image and predicting its 6D pose without requiring multiple stages or having to examine multiple hypotheses. Unlike a recently proposed single-shot technique for this task [ ...
2018Real-Time Seamless Single Shot 6D Object Pose Prediction
Pascal Fua, Bugra Tekin, Sudipta Sinha
We propose a single-shot approach for simultaneously detecting an object in an RGB image and predicting its 6D pose without requiring multiple stages or having to examine multiple hypotheses. Unlike a recently proposed single-shot technique for this task [ ...
IEEE2018Method, System and Device for Direct Prediction of 3D Body Poses from Motion Compensated Sequence
Pascal Fua, Vincent Lepetit, Bugra Tekin, Artem Rozantsev
A method for predicting three-dimensional body poses from image sequences of an object, the method performed on a processor of a computer having memory, the method including the steps of accessing the image sequences from the memory, finding bounding boxes ...
2017Structured Prediction of 3D Human Pose with Deep Neural Networks
Pascal Fua, Mathieu Salzmann, Isinsu Katircioglu, Vincent Lepetit, Bugra Tekin
Most recent approaches to monocular 3D pose estimation rely on Deep Learning. They either train a Convolutional Neural Network to directly regress from image to 3D pose, which ignores the dependencies between human joints, or model these dependencies via a ...
2016Direct Prediction of 3D Body Poses from Motion Compensated Sequences
Pascal Fua, Vincent Lepetit, Bugra Tekin, Artem Rozantsev
We propose an efficient approach to exploiting motion information from consecutive frames of a video sequence to recover the 3D pose of people. Previous approaches typically compute candidate poses in individual frames and then link them in a post-processi ...
2016Learning Separable Filters
Pascal Fua, Vincent Lepetit, Bugra Tekin, Roberto Rigamonti, Amos Sironi
Learning filters to produce sparse image representations in terms of overcomplete dictionaries has emerged as a powerful way to create image features for many different purposes. Unfortunately, these filters are usually both numerous and non-separable, mak ...
Ieee Computer Soc2015Learning Separable Filters with Shared Parts
Learned image features can provide great accuracy in many Computer Vision tasks. However, when the convolution filters used to learn image features are numerous and not separable, feature extraction becomes computationally demanding and impractical to use ...
2013