Computer Vision for Human-Computer Interaction Lab

The CV:HCI lab is part of the Institute for Anthropomatics and Robotics (IAR) of the Department of Computer Science at the Karlsruhe Institute of Technology.

The lab is directed by Prof. Dr. Rainer Stiefelhagen, who also supervises the KIT's Study Center for Visually Impaired Students (SZS). Together with the SZS, we develop new assistive technologies for visually impaired people. We also have a close collaboration with the Fraunhofer IOSB in Karlsruhe.

Our research focuses on the perception of people with applications in the following areas:

Perception of People for HCI

Vision for the Seeing Impaired

Health Care

Image and Video Analysis

NEWS

Update - ZEISS Hackathon postponed

We are sorry to tell you that this year's ZEISS Computer Vision Hackathon - Next Gen Computer Vision which is co-organised by our team needs to be postponed to September 2020 due to the current health situation.

Presentation at ICCV 2019

We were invited to present our paper by A. Roitberg written in collaboration with M. Martin from Fraunhofer IOSB features Drive&Act, the first large-scale dataset for fine-grained driver activity recognition.

We did it again!

At the 30th British Machine Vision Conference (BMVC) 2019 in Cardiff, our team won again the Best Industry Paper Award for its work on Image Translations with Spatial Profile Loss.

Great news!

Our work on Self-Supervised Learning of Face Representations received the best paper award at IEEE Automatic Face and Gesture Recognition 2019

Authors: Vivek Sharma, Makarand Tapaswi, Saquib Sarfraz, and Rainer Stiefelhagen

No 'Computer Vision for Human Computer Interaction' lecture in WS 19/20

Please be informed that our 'Computer Vision for Human Computer Interaction' lecture will not take place next winter semester. However, it will be resumed in WS 20/21.

We have two paper accepted at CVPR 2019!

The paper by M. Haurilet et al. presents a novel model based on a graph-traversal scheme for Visual Reasoning. The architecture searches relevant nodes in the scene graph to find information for answering the current question.

The paper by M.S. Sarfraz et al. introduces a highly-efficient approach for clustering using first neighbour relations. In comparison to other clustering algorithms, FINCH does not require any hyper-parameters, but is able to deduce the number of clusters automatically.

New lecture starting in summer 2018

We will offer a new lecture 'Deep Learning for Computer Vision' from this summer semester on.

Great news - We have two paper accepted at CVPR 2018; one of the top computer vision conferences!

The paper by S. Sarfraz et al. presents a novel approach for person re-identification and an unsupervised re-ranking method for retrieval applications.

The paper by V. Sharma et al. presents a novel CNN architecture that can enhance image-specific details via dynamic enhancement filters with the overall all goal to improve classification.

Important news - Update!

We have moved back to
Vincenz-Prießnitz-Str. 3.

Great news - Award won at CVPR Workshop 2017!

Monica Haurilet and Ziad Al-Halah participated in the textbook question answering challenge and won the first place on the text-based track and came second in the diagram-based track.
The winners were announced in CVPR17 Workshop for visual understanding across modalities - read more

2016_085_Testlabor_fuer_barrierefreien_Zugang_zu_Informationen-2.jpg

Inauguration of Accessibitlity Lab at SZS

Our new test lab for a barrier-free access to information for visually imparired persons was inaugurated on 3rd June 2016.

Best Industry Paper Award

At the 26th British Machine Vision Conference (BMVC) 2015, our team received the best industry paper award for the work on thermal-visible face recognition
Read more

Foto Al-Halah Presiverleihung ICVSS 2015

Best Presentation Award

At the 9th International Computer Vision Summer School (ICVSS) 2015, our team member Ziad Al-Halah received the best presentation prize for his work on Hierarchical Transfer of Semantic Attributes.

MIT Technology Review, July 2015

MIT Technology Review featured an article on our thermal visible face matching work in July 2015. Read more how 'Deep Neural Nets Can Now Recognize Your Face in Thermal Images'

Read more in 'In the Press'

"A Mobility and Navigational Aid for Visually Impaired Persons"

New lecture starting in summer 2014

We offer a new lecture 'Assistive Technologies for Visually Impaired Persons' from this semester on. Further details

IBM Best Student Paper Award

At the 22nd International Conference on Pattern Recognition (ICPR) Prof. Stiefelhagen's team received the IBM Best Student Paper Award in the Track 'Pattern Recognition and Machine Learning' for the work on "High-Level Semantics in Transfer Metric Learning".

Further details

Google Faculty Research Award Our research group receives a Google Research Award for its work on "A Mobility and Navigational Aid for Visually Impaired Persons". The "Google Faculty Research Award" is endowed with 83.000 USD for supporting research in computer science, engineering and related disciplines.
Further details.

How technology analyses faces @ CeBIT 2013

The video production team from the Department of Informatics visited our booth at the CeBIT 2013 and recorded a presentation of our demos there. You can watch it in their video channel KITInformatik.

CeBIT: CVHCI in the press

We received some nice press coverage after CeBIT. Check it out:

on heute.de
on itworld.com

Check out our project pages to learn more on our research on face analysis and person identification in multimedia.