Davide Scaramuzza is professor of robotics and perception at both departments of Neuroinformatics (University of Zurich & ETH Zurich) and Informatics (University of Zurich), where he does research at the intersection of robotics and computer vision. He did his PhD in robotics and computer vision at ETH Zurich (with Roland Siegwart) and a postdoc at the University of Pennsylvania (with Vijay Kumar and Kostas Daniilidis). From 2009 to 2012, he led the European project sFly, which introduced the PX4 autopilot and pioneered visual-SLAM–based autonomous navigation of micro drones. From 2015 to 2018 he was part of the DARPA FLA program. For his research contributions, he was awarded the prestigious IEEE Robotics and Automation Society Early Career Award, the Misha Mahowald Neuromorphic Engineering Award, the SNSF-ERC Starting Grant (equivalent to NSF Career Award), Google, Intel, Qualcomm, and KUKA awards, as well as several conference and journal paper awards (e.g., IEEE Trans. of Robotics Best Paper Award in 2018). He coauthored the book “Introduction to Autonomous Mobile Robots” (published by MIT Press) and more than 100 papers on robotics and computer vision. In 2015, he cofounded a venture, called Zurich-Eye, dedicated to visual-inertial navigation solutions for mobile robots, which today is Facebook-Oculus Zurich. He was also the strategic advisor of Dacuda, an ETH spinoff dedicated to inside-out VR solutions, which today is Magic Leap Zurich. Many aspects of his research have been prominently featured in the popular press, such as The New York Times, Discovery Channel, BBC, IEEE Spectrum, MIT Technology Review.

Jean-François Lalonde, Ph.D., is an Associate Professor in the Electrical and Computer Engineering Department at Université Laval (Québec City) since 2013. Previously, he was a Post-Doctoral Associate at Disney Research, Pittsburgh. He received a Ph.D. in Robotics from Carnegie Mellon University in 2011. His thesis, titled "Understanding and Recreating Appearance under Natural Illumination," won the CMU School of Computer Science Distinguished Dissertation Award. His research interests lie at the intersection of computer vision, computer graphics, and machine learning. In particular, he is interested in exploring how physics-based models and data-driven machine learning techniques can be unified to better understand, model, interpret, and recreate the richness of our visual world. To this end, he has published more than 60 research papers, including several papers on the problem of lighting estimation from images. His group has also captured and published the largest datasets of indoor and outdoor high dynamic range wide-angle and omnidirectional images, freely available for research. He is actively involved in bringing research ideas to commercial products, as demonstrated by his 8 patents, his several technology transfers with large companies such as Adobe, and his involvement with startups including Geomagical Labs (San Francisco, acquired by IKEA) and TandemLaunch (Montreal).

Kristen Grauman is a Professor in the Department of Computer Science at the University of Texas at Austin and a Research Scientist in Facebook AI Research (FAIR). Her research in computer vision and machine learning focuses on visual recognition and search. Before joining UT Austin in 2007, she received her Ph.D. at MIT. She is an IEEE Fellow, AAAI Fellow, Sloan Fellow, and a recipient of NSF CAREER and ONR Young Investigator awards, the PAMI Young Researcher Award in 2013, the 2013 Computers and Thought Award from the International Joint Conference on Artificial Intelligence (IJCAI), and the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2013. She and her collaborators were recognized with several best paper awards, including a 2011 Marr Prize and 2017 Helmholtz Prize. She currently serves as an Associate Editor-in-Chief for the Transactions on Pattern Analysis and Machine Intelligence (PAMI), and previously served as a Program Chair of CVPR 2015 and NeurIPS 2018.

Daniel Cremers studied physics and mathematics in Heidelberg, Indiana and New York. He received a PhD in Computer Science (2002) from the University of Mannheim, Germany. Subsequently he spent two years as a postdoctoral researcher at the University of California at Los Angeles (UCLA) and one year as a permanent researcher at Siemens Corporate Research in Princeton, NJ. From 2005 until 2009 he was associate professor at the University of Bonn. Since 2009 he holds the Chair of Computer Vision and Artificial Intelligence at the Technical University of Munich. His publications received numerous awards, including the 'Best Paper of the Year 2003' (Int. Pattern Recognition Society), the 'Olympus Award 2004' (German Soc. for Pattern Recognition) and the '2005 UCLA Chancellor's Award for Postdoctoral Research'. For pioneering research he received five grants from the European Research Council, including a Starting Grant (2009), a Consolidator Grant (2015) and an Advanced Grant (2020). Professor Cremers has served as associate editor for several journals. In 2018 he organized the largest ever European Conference on Computer Vision in Munich with over 3300 delegates. He is member of the Bavarian Academy of Sciences and Humanities. He is honorary member of the Dagstuhl Scientific Directorate. In December 2010 he was listed among "Germany's top 40 researchers below 40" (Capital). On March 1st 2016, Prof. Cremers received the Gottfried Wilhelm Leibniz Award, the biggest award in German academia. He is co-founder of several companies, most recently the high-tech startup Artisense.

Dr. Matthias Nießner is a Professor at the Technical University of Munich where he leads the Visual Computing Lab. Before, he was a Visiting Assistant Professor at Stanford University. Prof. Nießner’s research lies at the intersection of computer vision, graphics, and machine learning, where he is particularly interested in cutting-edge techniques for 3D reconstruction, semantic 3D scene understanding, video editing, and AI-driven video synthesis. In total, he has published over 70 academic publications, including 22 papers at the prestigious ACM Transactions on Graphics (SIGGRAPH / SIGGRAPH Asia) journal and 26 works at the leading vision conferences (CVPR, ECCV, ICCV); several of these works won best paper awards, including at SIGCHI’14, HPG’15, SPG’18, and the SIGGRAPH’16 Emerging Technologies Award for the best Live Demo. Prof. Nießner’s work enjoys wide media coverage, with many articles featured in main-stream media including the New York Times, Wall Street Journal, Spiegel, MIT Technological Review, and many more, and his was work led to several TV appearances such as on Jimmy Kimmel Live, where Prof. Nießner demonstrated the popular Face2Face technique; Prof. Nießner’s academic Youtube channel currently has over 5 million views. For his work, Prof. Nießner received several awards: he is a TUM-IAS Rudolph Moessbauer Fellow (2017 – ongoing), he won the Google Faculty Award for Machine Perception (2017), the Nvidia Professor Partnership Award (2018), as well as the prestigious ERC Starting Grant 2018 which comes with 1.500.000 Euro in research funding; in 2019, he received the Eurographics Young Researcher Award honoring the best upcoming graphics researcher in Europe. In addition to his academic impact, Prof. Nießner is a co-founder and director of Synthesia Inc., a brand-new startup backed by Marc Cuban, whose aim is to empower storytellers with cutting-edge AI-driven video synthesis.

Taco Cohen is a machine learning research scientist at Qualcomm AI Research in Amsterdam and a PhD student at the University of Amsterdam, supervised by Prof. Max Welling. He was a co-founder of Scyfer, a company focused on active deep learning, acquired by Qualcomm in 2017. He holds a BSc in theoretical computer science from Utrecht University and a MSc in artificial intelligence from the University of Amsterdam. His research is focused on deep learning based source compression as well as understanding and improving deep representation learning, in particular learning of equivariant and disentangled representations, data-efficient deep learning, learning on non-Euclidean domains, and applications of group representation theory and non-commutative harmonic analysis. He has done internships at Google DeepMind (working with Geoff Hinton) and OpenAI. He received the 2014 University of Amsterdam thesis prize, a Google PhD Fellowship, ICLR 2018 best paper award for “Spherical CNNs”, and was named one of 35 innovators under 35 in Europe by MIT in 2018.

Tomas Pajdla (Czech Technical University in Prague) is an Associate Professor at the CTU in Prague. He works in geometry and algebra of computer vision and robotics, 3D reconstruction, visual localization, place recognition and industrial vision. He contributed to introducing epipolar geometry of panoramic cameras, non-central camera models generated by linear mapping, generalized epipolar geometries, to developing solvers for minimal problems in structure from motion, solving image matching problem and to image-based localization. He co-authored works awarded prizes at OAGM 1998 and 2013, BMVC 2002, ACCV 2014 and ICCV 2019. He was a program chair/organizer of ECCV 2004, 2014, 3DV 2018, and numerous and tutorials CVPR. ICCV, ECCV workshops, e.g. CVVT 2010-2018, OMNIVIS 2007 and Minimal 2015.

Hirochika Fujiki received his M.Eng degree in Electronic and Electrical Engineering from Chiba University in March 31, 2017. After graduation, H. Fujiki joined the Ricoh Company and he is currently a member of the Smart Vision Business Group, the unit behind RICOH THETA, the most popular hand-held panorama imaging device in the market. Mr. Fujiki develops advanced features using 360 imaging for several Ricoh products and services, such as 360 virtual tours. Recently, he developed auto-cropping function that produces snapshots with beautiful and balanced composition from 360 photos, automatically. This became a novel Computer Vision feature released for RICOH360-Tours service. Mr. Fujiki also works on developing deep learning applications leveraging the company's massive dataset of real estate images. On such application is the estimation of room layouts from 360 images. His passion continues to drive him to contribute to academic and industrial 360 imaging.

Rajat Aggarwal is the CEO at DreamVu and received his BS and MS from IIIT Hyderabad in 2017 with a specialization in computer vision and computational photography. His path-breaking research on computational cameras led to several publications and patents starting from his early undergraduate days. His publication in CVPR’16 was a breakthrough in the field of computational photography and eventually became the seed for DreamVu. Rajat is now driving the market adoption of omnidirectional stereo cameras through novel inventions in the optics at DreamVu. He also worked with prestigious research groups like MIT Media Lab’s Camera Culture group inventing low-cost medical devices. A hardcore inventor at heart, Rajat is a true believer in the power of optics to solve some of the trickiest challenges in sensing and perception for humans and machines.

Ganesh Sistu is currently working as a Computer Vision and Deep Learning Expert for Automated Driving at Valeo Ireland. He has over 10 years of R&D experience in image analysis, computer vision, machine learning and deep learning. Prior to joining Valeo, he worked at Robert Bosch, Stryker and L&T technologies. His current area of research is multitask learning and visual perception. He has 20 publications including premier venues such as ICCV, ITSC, VISAPP, CVPR(w) and NeurIPS(w). He has 15 patents in medical & microscopic imaging, video surveillance and automated parking.

Sing Bing Kang received his Ph.D. degree in robotics from Carnegie Mellon University in 1994. He is currently Distinguished Scientist at Zillow Group. His research interests are computational photography and image-based modeling. Sing Bing has coedited two books ("Panoramic Vision" and "Emerging Topics in Computer Vision") and coauthored two books ("Image-Based Rendering" and "Image-Based Modeling of Plants and Trees"). On the community service front, he has served as Area Chair for the major computer vision conferences and as papers committee member for SIGGRAPH and SIGGRAPH Asia. Sing Bing also serves as editor for the Springer ACVPR book series. He was Program Chair for ACCV 2007 and CVPR 2009, and was Associate Editor-In-Chief for IEEE Transactions on Pattern Analysis and Machine Intelligence from 2010-2014. He is a Fellow of the IEEE.

Gang Hua is the Vice President and Chief Scientist of Wormpex AI Research. His research focuses on computer vision, pattern recognition, machine learning, robotics, towards general Artificial Intelligence, with primary applications in cloud and edge intelligence, and currently with a focus on new retail intelligence.

Before that, he served in various roles at Microsoft (2015-18) as the Science/Technical Adviser to the CVP of the Computer Vision Group, Director of Computer Vision Science Team in Redmond and Taipei ATL, and Senior Principal Researcher/Research Manager at Microsoft Research . He was an Associate Professor at Stevens Institute of Technology (2011-15). During 2014-15, he took an on leave and worked on the Amazon-Go project. He was a Visiting Researcher (2011-14) and a Research Staff Member (2010-11) at IBM Research T. J. Watson Center, a Senior Researcher (2009-10) at Nokia Research Center Hollywood, and a Scientist (2006-09) at Microsoft Live Labs Research. He received his Ph.D. degree in ECE from Northwestern University in 2006.

He is an IEEE Fellow, an IAPR Fellow, and an ACM Distinguished Scientist for contributions to Multimedia and Computer Vision. He is the recipient of the 2015 IAPR Young Biometrics Investigator Award for contributions to Unconstrained Face Recognition from Images and Videos. He serves as a Program Chair for CVPR19&22. To date, He has published more than 170 peer reviewed papers. He holds 20 issued U.S Patents and also has more than 20 more U.S. Patents Pending.