Events & Talks

Perceiving Systems Talk Maria Kolos 14-07-2021 TRANSPR: Transparency Ray-Accumulating Neural 3D Scene Point Renderer We propose and evaluate a neural point-based graphics method that can model semi-transparent scene parts. Similarly to its predecessor pipeline, ours uses point clouds to model proxy geometry, and augments each point with a neural descriptor. Additionally, a learnable transparency value is introduced in our approach for each point. Our neural rendering procedure consists of two steps. Firstly, the point cloud is rasterized using ray grouping into a multi-channel image. This is followed by the neural rendering step that "translates" the rasterized image into an RGB output using a learnable ... Qianli Ma

Talk Prof. Read, Jenny 05-07-2021 Stereo vision in humans and insects

IS Colloquium Prof. Margarita Chli 28-06-2021 Teaching Robots to See – Challenges and Developments in Robotic Vision As vision plays a key role in how we interpret a situation, developing vision-based perception for robots promises to be a big step towards robotic intelligence. This talk will briefly discuss some of the biggest challenges we are faced with all the way from robust localization and mapping, to dense scene representation for path planning, and collaborative perception. With effective robot collaboration featuring as a key scientific challenge in the field, the talk will focus on this topic describing our recent progress in this area at the Vision for Robotics Lab of ETH Zurich (http://www.v4... Katherine J. Kuchenbecker Oliwia Gust

Perceiving Systems Talk Nataniel Ruiz 14-06-2021 Using Generative Models for Faces to Test Neural Networks Most machine learning models are validated on fixed datasets. This can give an incomplete picture of the capabilities and weaknesses of the model. Such weaknesses can be revealed at test time in the real world with dire consequences. In order to alleviate this issue, simulators can be controlled in a fine-grained manner using interpretable parameters to explore the semantic image manifold and discover such weaknesses before deploying a model. Also, in recent years there have been important advances in generative models for computer vision resulting in realistic face generation and manipulat... Timo Bolkart

Perceiving Systems Talk Peizhuo Li 10-06-2021 Learning Skeletal Articulations with Neural Blend Shapes Animating a newly designed character using motion capture (mocap) data is a long standing problem in computer animation. A key consideration is the skeletal structure that should correspond to the available mocap data, and the shape deformation in the joint regions, which often requires a tailored, pose-specific refinement. In this work, we develop a neural technique for articulating 3D characters using enveloping with a pre-defined skeletal structure which produces high quality pose dependent deformations. Our framework learns to rig and skin characters with the same articulation structure... Hongwei Yi

Rationality Enhancement Conference 09-06-2021 - 13-06-2021 Life Improvement Science Conference Life Improvement Science (LIS) is an emerging transdisciplinary research field that investigates how we can help people do more good in better ways (well-doing). Falk Lieder Mike Prentice Pin-Zhen Chen Anastasia Lado Sierra Kaiser Victoria Amo

Perceiving Systems Talk Marc Habermann 01-06-2021 Real-time Deep Dynamic Characters Animatable and photo-realistic virtual 3D characters are of enormous importance nowadays. However, generating realistic characters still requires manual intervention, expensive equipment, and the resulting characters are either difficult to control or not realistic. Therefore, the goal of the work, that is presented within the talk, is to learn digital characters which are both realistic and easy to control and can be learned directly from a multi-view video. To this end, I will introduce a deep videorealistic 3D human character model displaying highly realistic shape, motion, and dynamic a... Yinghao Huang Chun-Hao Paul Huang

Perceiving Systems Talk Chloe LeGendre 11-05-2021 Lighting Virtual Objects using Machine Learning Compositing rendered, virtual objects into photographs or videos is a fundamental technique in mixed reality, visual effects, and film production. For truly convincing and seamless composites, the subjects must be rendered with lighting that matches that of the target footage. For instance, a rendered object that is too bright, too dark, or lit from a direction inconsistent with other objects in the scene will look out of place. As such, in this talk I will introduce two recent machine learning based approaches for lighting estimation used for improving the realism of augmented reality (AR)... Victoria Fernandez Abrevaya

Perceiving Systems Talk Justus Thies 15-04-2021 Neural Capture & Synthesis The main theme of my work is to capture and to (re-)synthesize the real world using commodity hardware. It includes the modeling of the human body, tracking, as well as the reconstruction and interaction with the environment. The digitization is needed for various applications in AR/VR as well as in movie (post-)production. Teleconferencing and remote collaborative working in VR is of high interest since it is the next evolution step of how people communicate. A realistic reproduction of appearances and motions is key for such applications. Capturing natural motions and expressions as well ... Ahmed Osman

Perceiving Systems Talk Gyeongsik Moon 12-04-2021 Expressive Whole-Body 3D Multi-Person Pose and Shape Estimation from a Single Image Human is the most centric and interesting object in our life: many human-centric techniques and studies have been proposed from both industry and academia, such as virtual try-on, 3D personal avatar, and marker-less motion capture in the movie/game industry, including AR/VR. Recovery of accurate 3D geometry of humans (i.e., 3D human pose and shape) is a key component of the human-centric techniques and studies. In particular, the 3D pose and shape of multiple persons can deliver relative 3D location between persons. Also, the 3D pose and shape of the whole body, which includes hands and fac... Chun-Hao Paul Huang

Perceiving Systems Talk Angjoo Kanazawa 08-04-2021 Pushing the Boundaries of Novel View Synthesis 2020 was a turbulent year, but for 3D learning it was a fruitful one with lots of exciting new tools and ideas. In particular, there have been many exciting developments in the area of coordinate based neural networks and novel view synthesis. In this talk I will discuss our recent work on single image view synthesis with pixelNeRF, which aims to predict a Neural Radiance Field (NeRF) from a single image. I will discuss how NeRF representation allows models like pixel-aligned implicit functions (PiFu) to be trained without explicit 3D supervision and the importance of other key design fact... Qianli Ma

Perceiving Systems Talk Meng Zhang 01-04-2021 Hair & garment synthesis using deep learning method For both AR and VR applications, there is a strong motivation to generate virtual avatars with realistic hairs and garments that are the two most significant elements to personify any character. However, due to the complex structures and ever-changing fashion styles, modeling hairs and garments still remain tedious and expensive as they require considerable professional effort. My research interest focuses on deep learning methods in 3D modeling, rendering, and animation, especially to synthesis high-quality hairs and garments with plausible details. In this talk, I will present the progres... Jinlong Yang

Perceiving Systems Talk Garvita Tiwari 25-02-2021 Learning Size-Sensitive Clothing Model From Real Data 3D Human modeling has numerous applications in AR/VR, entertainment, the fashion industry and has been a challenging task, due to variation in human motion, body shape, style of clothing. One of the main challenges in human modeling is clothing, because of the complex behavior of clothing in the real world, lack of large scale dataset, etc. In this talk, I will talk about the motivation of learning from real-world data and present my previous work on size sensitive clothing model and 3d clothing parsing.

Perceiving Systems Talk Leonidas Guibas 22-02-2021 Joint Learning Over Visual and Geometric Data Many challenges remain in applying machine learning to domains where obtaining massive annotated data is difficult. We discuss approaches that aim to reduce supervision load for learning algorithms in the visual and geometric domains by leveraging correlations among data as well as among learning tasks -- what we call joint learning. The basic notion is that inference problems do not occur in isolation but rather in a "social context" that can be exploited to provide self-supervision by enforcing consistency, thus improving performance and increasing sample efficiency. An example is voting ... Qianli Ma

Perceiving Systems Talk Ruilong Li 10-02-2021 AI Choreographer: Learn to dance with AIST++ In this work, we present a transformer-based learning framework for 3D dance generation conditioned on music. We carefully design our network architecture and empirically study the keys for obtaining qualitatively pleasing results. In addition, we propose a new dataset of paired 3D motion and music called AIST++, which contains 1.1M frames of 3D dance motion in 1408 sequences, covering 10 genres of dance choreographies and accompanied with multi-view camera parameters. To our knowledge it is the largest dataset of this kind. Yuliang Xiu

Physical Intelligence Talk Dr. Gündoğ Yücesan 09-02-2021 Phosphonate-MOFs,-HOFs: Next generation of microporous compounds Among the other metal organic framework (MOF) familieis, phosphonic acids provide the richest metal binding for MOF synthesis, and they are known to exhibit exceptional thermal and chemical stabilities. Due to the synthetic difficulties, the total number of microporous phosphonate-MOFs are still limited in the literature. In this work, we provide design and synthesis strategies to form semiconductive, proton conductive microporous MOFs and hydrogen bonded organic frameworks (HOFs) constructed using structure directing arylphosphonic acids. Metin Sitti

Talk Prof. Wolfe, Jeremy M. 04-02-2021 How do we find what we are looking for? The Guided Search 6.0 model

Perceiving Systems Talk Shruti Agarwal 28-01-2021 Creating, Weaponizing, and Detecting Deep Fakes The past few years have seen a startling and troubling rise in the fake-news phenomena in which everyone from individuals to nation-sponsored entities can produce and distribute misinformation. The implications of fake news range from a misinformed public to an existential threat to democracy, and horrific violence. At the same time, recent and rapid advances in machine learning are making it easier than ever to create sophisticated and compelling fake images, videos, and audio recordings, making the fake-news phenomena even more powerful and dangerous. These AI-synthesized media (so-called... Jinlong Yang

Symposium 27-01-2021 - 28-01-2021 IMPRS-IS 2021 Symposium Keynotes The 2021 IMPRS-IS Interview Symposium will feature two keynote presentations open to our entire community. Speakers include Dr. Ulrike von Luxburg of the University of Tübingen and Dr. Christoph Keplinger representing the Max Planck Institute for Intelligent Systems. Leila Masri Sara Sorce

Perceiving Systems Talk Yixin Chen 27-01-2021 Towards a more holistic understanding of scene, object, and human Humans, even young infants, are adept at perceiving and understanding complex indoor scenes. Such an incredible vision system relies on not only the data-driven pattern recognition but also roots from the visual reasoning system, known as the core knowledge, that facilitates the 3D holistic scene understanding tasks. This talk discusses how to employ physical common sense and human-object interaction to bridge scene and human understanding and how the part-level 3D affordance perception may lead to a more fine-grained human-object interaction modeling. Future directions may be extended to d... Dimitris Tzionas

Talk Zorah Lähner 21-01-2021 Non-Rigid Shape Correspondence through Deformation Solving for 3D correspondences beyond isometries has made tremendous progress in recent years, much of it due to (deep) learning. However, not all applications provide the necessary training data. This talk will focus on how far we can take the results without learning. I will present a line of work that poses the non-rigid shape registration problem in terms of physical and non-physical deformation energies. Our work aims to combine extrinsic and intrinsic measures to overcome typical shortcomings of both. We use Functional Maps and Markov Chain Monte Carlo initialization to handle all kin... Jinlong Yang

Perceiving Systems Talk Zorah Lähner 21-01-2021 Non-Rigid Shape Correspondence through Deformation Solving for 3D correspondences beyond isometries has made tremendous progress in recent years, much of it due to (deep) learning. However, not all applications provide the necessary training data. This talk will focus on how far we can take the results without learning. I will present a line of work that poses the non-rigid shape registration problem in terms of physical and non-physical deformation energies. Our work aims to combine extrinsic and intrinsic measures to overcome typical shortcomings of both. We use Functional Maps and Markov Chain Monte Carlo initialization to handle all kin... Jinlong Yang

Talk Dr. Christian Waiblinger 02-01-2021 Adaptive perception and behavior in a changing sensory environment

Perceiving Systems Talk Raquel Urtasun 14-12-2020 A Future with Self-Driving Vehicles We are on the verge of a new era in which robotics and artificial intelligence will play an important role in our daily lives. Self-driving vehicles have the potential to redefine transportation as we understand it today. Our roads will become safer and less congested, while parking spots will be repurposed as leisure zones and parks. However, many technological challenges remain as we pursue this future. In this talk I will showcase the latest advancements made by Uber Advanced Technologies Group’s in the quest towards self-driving vehicles at scale. Qianli Ma

Talk Nanshu Lu 18-11-2020 Electronic Tattoos for Mobile Sensing and Therapeutics Merging human body with electronics and machines can enable internet of health (IoH), human-machine interface (HMI), as well as augmented human capabilities. However, bio-tissues are soft, curvilinear and dynamic whereas wafer-based electronics are hard, planar, and rigid. Over the past decade, stretchable high-performance inorganic electronics blossom as a result of innovative structural designs and fabrication processes. In particular, epidermal electronics, a.k.a. electronic tattoos (e-tattoos) represent a class of noninvasive stretchable circuits, sensors, and stimulators that are ultra... Metin Sitti

Haptic Intelligence PhD Thesis Defense 06-10-2020 Delivering Expressive and Personalized Fingertip Tactile Cues Wearable haptic devices have seen growing interest in recent years, but providing realistic tactile feedback is not a challenge that is soon to be solved. Daily interactions with physical objects elicit complex sensations at the fingertips. Furthermore, human fingertips exhibit a broad range of physical dimensions and perceptive abilities, adding increased complexity to the task of simulating haptic interactions in a compelling manner. However, as the applications of wearable haptic feedback grow, concerns of wearability and generalizability often persuade tactile device designers to simpli... Katherine J. Kuchenbecker Eric Young

Perceiving Systems Talk Daniel Haun 05-10-2020 The phenotyping revolution One of the most striking characteristics of human behavior in contrast to all other animal is that we show extraordinary variability across populations. Human cultural diversity is a biological oddity. More specifically, we propose that what makes humans unique is the nature of the individual ontogenetic process, that results in this unparalleled cultural diversity. Hence, our central question is: How is human ontogeny adapted to cultural diversity and how does it contribute to it? This question is critical, because cultural diversity does not only entail our predominant mode of adaptation ... Timo Bolkart

Perceiving Systems Talk Noah Snavely 02-10-2020 Reconstructing the Plenoptic Function Imagine a futuristic version of Google Street View that could dial up any possible place in the world, at any possible time. Effectively, such a service would be a recording of the plenoptic function—the hypothetical function described by Adelson and Bergen that captures all light rays passing through space at all times. While the plenoptic function is completely impractical to capture in its totality, every photo ever taken represents a sample of this function. I will present recent methods we've developed to reconstruct the plenoptic function from sparse space-time samples of photos—inclu...

Autonomous Vision Event 28-09-2020 - 01-10-2020 German Conference on Pattern Recognition DAGM-GCPR 2020 in Tübingen The 42nd German Conference on Pattern Recognition (DAGM-GCPR 2020), the 25th International Symposium on Vision, Modeling and Visualization (VMV 2020) and the 10th Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM 2020) will for the first time be co-located in Tübingen this year! Andreas Geiger

Event 31-08-2020 Scientific Symposium 2020 All current and former employees and friends of the Max Planck Institute fo Intelligent Systems and Cyber Valley are welcome to attend this event. If you have any questions, please contact our Event Manager - Oliwia Gust (oliwia.gust@cyber-valley.de) Michael Black Katherine J. Kuchenbecker Bernhard Schölkopf Metin Sitti Florian Mayer Matthias Tröndle

Perceiving Systems Talk Daniel Holden 10-08-2020 Functions, Machine Learning, and Game Development Game Development requires a vast array of tools, techniques, and expertise, ranging from game design, artistic content creation, to data management and low level engine programming. Yet all of these domains have one kind of task in common - the transformation of one kind of data into another. Meanwhile, advances in Machine Learning have resulted in a fundamental change in how we think about these kinds of data transformations - allowing for accurate and scalable function approximation, and the ability to train such approximations on virtually unlimited amounts of data. In this talk I will p... Abhinanda Ranjit Punnakkal

Perceiving Systems Talk Vittorio Ferrari 07-08-2020 Our Recent Research on 3D Deep Learning I will present three recent projects within the 3D Deep Learning research line from my team at Google Research: (1) a deep network for reconstructing the 3D shape of multiple objects appearing in a single RGB image (ECCV'20). (2) a new conditioning scheme for normalizing flow models. It enables several applications such as reconstructing an object's 3D point cloud from an image, or the converse problem of rendering an image given a 3D point cloud, both within the same modeling framework (CVPR'20); (3) a neural rendering framework that maps a voxelized object into a high quality image. It re... Yinghao Huang Arjun Chandrasekaran

Perceiving Systems Talk Antonio Torralba 28-07-2020 Learning from vision, touch and audition Babies learn with very little supervision, and, even when supervision is present, it comes in the form of an unknown spoken language that also needs to be learned. How can kids make sense of the world? In this work, I will show that an agent that has access to multimodal data (like vision, audition or touch) can use the correlation between images and sounds to discover objects in the world without supervision. I will show that ambient sounds can be used as a supervisory signal for learning to see and vice versa (the sound of crashing waves, the roar of fast-moving cars – sound conveys impor... Arjun Chandrasekaran

Haptic Intelligence Talk Yitian Shao 28-07-2020 Tactile Sensing, Information, and Feedback via Wave Propagation A longstanding goal of engineering has been to realize haptic interfaces that can convey realistic sensations of touch, comparable to signals presented via visual or audio displays. Today, this ideal remains far from realization, due to the difficulty of characterizing and electronically reproducing the complex and dynamic tactile signals that are produced during even the simplest touch interactions. In this talk, I will present my work on capturing whole-hand tactile signals, in the form of mechanical waves, produced during natural hand interactions. I will describe how I characterized the... Katherine J. Kuchenbecker

Event 24-07-2020 2020 Intelligent Systems Summer Colloquium (Virtual Event) MPI-IS cordially invites you to attend the 2020 Intelligent Systems Summer Colloquium

Physical Intelligence Talk Dr. Dieter Nees 22-07-2020 Large-Area Fabrication of Nanoscale Features by UV-NIL @ JR MATERIALS Roll-to-roll UV nanoimprint lithography (R2R-UV-NIL) gains increasing industrial interest for large area nano- and micro-structuring of flexible substrates because it combines nanometer resolution with many square meter per minute productivity. Small-area masters of functional nano and micro surface structures are readily available by various lithographic techniques like e.g. UV-, e-beam- or interference lithography. However, the upscaling of small-area nano- and micro-structured masters into medium size roller molds – often called shims - for R2R-UV-NIL production still remains a bottlene...

Perceiving Systems Talk Artsiom Sanakoyeu 22-07-2020 Learning Dense Correspondences for Animals with limited supervision and Improving Generalization for Deep Metric Learning Learning the embedding space, where semantically similar objects are located close together and dissimilar objects far apart, is a cornerstone of many computer vision applications. Existing approaches usually learn a single metric in the embedding space for all available data points,which may have a very complex non-uniform distribution with different notions of similarity between objects, e.g. appearance, shape, color or semantic meaning. We approach this problem by using the embedding space more efficiently by jointly splitting the embedding space and data into K smaller sub-problems. It ... Nikos Athanasiou

Perceiving Systems Talk Angela Dai 16-07-2020 Towards Commodity 3D Scanning for Content Creation In recent years, commodity 3D sensors have become widely available, spawning significant interest in both offline and real-time 3D reconstruction. While state-of-the-art reconstruction results from commodity RGB-D sensors are visually appealing, they are far from usable in practical computer graphics applications since they do not match the high quality of artist-modeled 3D graphics content. One of the biggest challenges in this context is that obtained 3D scans suffer from occlusions, thus resulting in incomplete 3D models. In this talk, I will present a data-driven approach towards genera... Yinghao Huang

Perceiving Systems Talk William T. Freeman 13-07-2020 Learning from videos played forwards, backwards, fast, and slow How can we tell that a video is playing backwards? People's motions look wrong when the video is played backwards--can we develop an algorithm to distinguish forward from backward video? Similarly, can we tell if a video is sped-up? We have developed algorithms to distinguish forwards from backwards video, and fast from slow. Training algorithms for these tasks provides a self-supervised task that facilitates human activity recognition. We'll show these results, and applications of these unsupervised video learning tasks, including a method to change the timing of people in videos. Yinghao Huang

Perceiving Systems Talk Matthias Nießner 10-07-2020 Learning Non-rigid Optimization Applying data-driven approaches to non-rigid 3D reconstruction has been difficult, which we believe can be attributed to the lack of a large-scale training corpus. One recent approach proposes self-supervision based on non-rigid reconstruction. Unfortunately, this method fails for important cases such as highly non-rigid deformations. We first address this problem of lack of data by introducing a novel semi-supervised strategy to obtain dense interframe correspondences from a sparse set of annotations. This way, we obtain a large dataset of 400 scenes, over 390,000 RGB-D frames, and 2,537 d... Vassilis Choutas

Perceiving Systems Talk Dushyant Mehta 02-07-2020 Real-time Multi-person 3D Motion Capture with a Single RGB Camera In our recent work, XNect, we propose a real-time solution for the challenging task of multi-person 3D human pose estimation from a single RGB camera. To achieve real-time performance without compromising on accuracy, our approach relies on a new efficient Convolutional Neural Network architecture, and a multi-staged pose formulation. The CNN architecture is approx. 1.3x faster than ResNet-50, while achieving the same accuracy on various tasks, and the benefits extend beyond inference speed to a much smaller training memory footprint and a much higher training throughput. The proposed pose ... Yinghao Huang

Max Planck Lecture Yoshua Bengio 23-06-2020 Machine Learning for Covid-19 Risk Awareness from Contact Tracing The Covid-19 pandemic has spread rapidly worldwide, overwhelming manual contact tracing in many countries, resulting in widespread lockdowns for emergency containment. Large-scale digital contact tracing (DCT) has emerged as a potential solution to resume economic and social activity without triggering a second outbreak. Various DCT methods have been proposed, each making trade-offs between privacy, mobility restriction, and public health. Michael Black Bernhard Schölkopf Julia Braun Oliwia Gust

Max Planck Lecture Martin Zwierlein 16-06-2020 The sound of fermions Fermions, particles with half-integer spin like the electron, proton and neutron, obey the Pauli principle: They cannot share one and the same quantum state. This “anti social” behavior is directly observed in experiments with ultracold gases of fermionic atoms: Pauli blocking in momentum space for a free Fermi gas, and in real space in gases confined to an optical lattice. When fermions interact, new, rather “social” behavior emerges, i.e. hydrodynamic flow, superfluidity and magnetism. The interplay of Pauli’s principle and strong interactions poses great difficulties to our understanding...

Perceiving Systems Talk Scott Eaton 12-06-2020 Artists+AI: Figures, Form and other Fantastical Experiments in Deep Learning In this visual feast, Scott recounts results and revelations from four years of experimentation using machine learning as a ‘creative collaborator’ in his artistic process. He makes the case that AI, rather than rendering artists obsolete, will empower us and expand our creative horizons. In this visual feast, Scott shares an eclectic range of successes and failures encountered in his efforts to create powerful, but artistically controllable neural networks to use as tools to represent and abstract the human figure. Scott also gives a behinds-the-scenes look at creating the work for his... Ahmed Osman

Perceiving Systems Talk Srinath Sridhar 10-06-2020 Canonicalization for 3D Perception In this talk, I will introduce the notion of 'canonicalization' and how it can be used to solve 3D computer vision tasks. I will describe Normalized Object Coordinate Space (NOCS), a 3D canonical container that we have developed for 3D estimation, aggregation, and synthesis tasks. I will demonstrate how NOCS allows us to address previously difficult tasks like category-level 6DoF object pose estimation, and correspondence-free multiview 3D shape aggregation. Finally, I will discuss future directions including opportunities to extend NOCS for tasks like articulated and non-rigid shape and po... Timo Bolkart

IS Colloquium Manuel Gomez Rodriguez 09-06-2020 Institute Colloquium: A Spatiotemporal Epidemic Model to Quantify the Effects of Contact Tracing, Testing, and Containment Motivated by the current COVID-19 outbreak, we introduce a novel epidemic model based on marked temporal point processes that is specifically designed to make fine-grained spatiotemporal predictions about the course of the disease in a population. Our model can make use and benefit from data gathered by a variety of contact tracing technologies and it can quantify the effects that different testing and tracing strategies, social distancing measures, and business restrictions may have on the course of the disease. Building on our model, we use Bayesian optimization to estimate the risk of ex... Bernhard Schölkopf

Haptic Intelligence Talk Valerio Ortenzi 09-06-2020 Robotic Manipulation: a Focus on Object Handovers Humans perform object manipulation in order to execute a specific task. Seldom is such action started with no goal in mind. In contrast, traditional robotic grasping (first stage for object manipulation) seems to focus purely on getting hold of the object—neglecting the goal of the manipulation. In this light, most metrics used in robotic grasping do not account for the final task in their judgement of quality and success. Since the overall goal of a manipulation task shapes the actions of humans and their grasps, the task itself should shape the metric of success. To this end, I will pre... Katherine J. Kuchenbecker

Max Planck Lecture Hanieh Fattahi 09-06-2020 Towards spectro-microscopy at extreme limits This talk is devoted to modern methods for attosecond and femtosecond laser spectro-microscopy with the special focus on applications that require extreme spatial resolution. In the first part, I discuss how high-harmonic generation by high-energy, high-power light transients holds promise to deliver the required photon flux and photon energy for attosecond pump-probe spectroscopy at high spatiotemporal resolution in order to capture electron-dynamic in matter. I demonstrate the first prototype high-energy field synthesizer based on Yb:YAG, thin-disk laser technology for generating high...

Talk Aamir Ahmad 18-05-2020 AirCap – Aerial Outdoor Motion Capture In this talk I will present an overview and the latest results of the project Aerial Outdoor Motion Capture (AirCap), running at the Perceiving Systems department. AirCap's goal is to achieve markerless and unconstrained human motion capture (MoCap) in unknown and unstructured outdoor environments. To this end, we have developed a flying MoCap system using a team of autonomous aerial robots with on-board, monocular RGB cameras. Our system is endowed with a range of novel functionalities which was developed by our group over the last 3 years. These include, i) cooperative detection and track... Katherine J. Kuchenbecker

Perceiving Systems Talk Will Smith 15-05-2020 Deep inverse rendering in the wild In this talk I will consider the problem of scene-level inverse rendering to recover shape, reflectance and lighting from a single, uncontrolled, outdoor image. This task is highly ill-posed, but we show that multiview self-supervision, a natural lighting prior and implicit lighting estimation allow an image-to-image CNN to solve the task, seemingly learning some general principles of shape-from-shading along the way. Adding a neural renderer and sky generator GAN, our approach allows us to synthesise photorealistic relit images under widely varying illumination. I will finish by briefly de... Timo Bolkart

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