Search Results for author: Hafez Farazi

Found 12 papers, 10 papers with code

Semantic Prediction: Which One Should Come First, Recognition or Prediction?

1 code implementation6 Oct 2021 Hafez Farazi, Jan Nogga, and Sven Behnke

The ultimate goal of video prediction is not forecasting future pixel-values given some previous frames.

Decision Making Semantic Composition +1

Real-time Pose Estimation from Images for Multiple Humanoid Robots

1 code implementation6 Jul 2021 Arash Amini, Hafez Farazi, Sven Behnke

Pose estimation commonly refers to computer vision methods that recognize people's body postures in images or videos.

Pose Estimation

Local Frequency Domain Transformer Networks for Video Prediction

1 code implementation10 May 2021 Hafez Farazi, Jan Nogga, Sven Behnke

Although these models can predict the future frames, they rely entirely on these recurrent structures to simultaneously perform three distinct tasks: extracting transformations, projecting them into the future, and transforming the current frame.

Motion Segmentation Video Prediction

Motion Segmentation using Frequency Domain Transformer Networks

1 code implementation18 Apr 2020 Hafez Farazi, Sven Behnke

Self-supervised prediction is a powerful mechanism to learn representations that capture the underlying structure of the data.

Motion Segmentation Video Prediction

RoboCup 2019 AdultSize Winner NimbRo: Deep Learning Perception, In-Walk Kick, Push Recovery, and Team Play Capabilities

2 code implementations16 Dec 2019 Diego Rodriguez, Hafez Farazi, Grzegorz Ficht, Dmytro Pavlichenko, Andre Brandenburger, Mojtaba Hosseini, Oleg Kosenko, Michael Schreiber, Marcel Missura, Sven Behnke

Individual and team capabilities are challenged every year by rule changes and the increasing performance of the soccer teams at RoboCup Humanoid League.

Robotics

Utilizing Temporal Information in Deep Convolutional Network for Efficient Soccer Ball Detection and Tracking

1 code implementation5 Sep 2019 Anna Kukleva, Mohammad Asif Khan, Hafez Farazi, Sven Behnke

We first solve the detection task for an image using fully convolutional encoder-decoder architecture, and later, we use it as an input to our temporal models and jointly learn the detection task in sequences of images.

Game of Football

NimbRo Robots Winning RoboCup 2018 Humanoid AdultSize Soccer Competitions

1 code implementation5 Sep 2019 Hafez Farazi, Grzegorz Ficht, Philipp Allgeuer, Dmytro Pavlichenko, Diego Rodriguez, Andre Brandenburger, Mojtaba Hosseini, Sven Behnke

Over the past few years, the Humanoid League rules have changed towards more realistic and challenging game environments, which encourage teams to advance their robot soccer performances.

Robotics

Frequency Domain Transformer Networks for Video Prediction

1 code implementation1 Mar 2019 Hafez Farazi, Sven Behnke

The task of video prediction is forecasting the next frames given some previous frames.

Video Prediction

NimbRo-OP2X: Adult-sized Open-source 3D Printed Humanoid Robot

1 code implementation19 Oct 2018 Grzegorz Ficht, Hafez Farazi, André Brandenburger, Diego Rodriguez, Dmytro Pavlichenko, Philipp Allgeuer, Mojtaba Hosseini, Sven Behnke

Humanoid robotics research depends on capable robot platforms, but recently developed advanced platforms are often not available to other research groups, expensive, dangerous to operate, or closed-source.

Robotics

Real-Time Visual Tracking and Identification for a Team of Homogeneous Humanoid Robots

no code implementations15 Oct 2018 Hafez Farazi, Sven Behnke

The use of a team of humanoid robots to collaborate in completing a task is an increasingly important field of research.

Real-Time Visual Tracking

Location Dependency in Video Prediction

1 code implementation11 Oct 2018 Niloofar Azizi, Hafez Farazi, Sven Behnke

The task of video prediction requires analyzing the video frames, temporally and spatially, and constructing a model of how the environment evolves.

Video Prediction

Online Visual Robot Tracking and Identification using Deep LSTM Networks

no code implementations11 Oct 2018 Hafez Farazi, Sven Behnke

One of the challenges for achieving collaboration in a team of robots is mutual tracking and identification.

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