Events & Talks

Perceiving Systems Talk Ye Yuan 18-01-2022 Unified Simulation, Perception, and Generation of Human Behavior Understanding and modeling human behavior is fundamental to almost any computer vision and robotics applications that involve humans. In this talk, I will present a holistic approach to human behavior modeling and tackle its three essential aspects --- simulation, perception, and generation. I will show how the three aspects are deeply connected and how utilizing and improving one aspect can greatly benefit the other aspects. Since humans live in a physical world, we treat simulation as the foundation of our approach and start by developing a fundamental framework for representing human ... Hongwei Yi

Conference 12-01-2022 - 13-01-2022 Scientific Symposium All current and former employees and friends of the Max Planck Institute for Intelligent Systems and Cyber Valley are welcome to attend this event. If you have any questions, please contact Cyber Valley Research Coordinator - Florian Mayer (florian.mayer@cyber-valley.de) Bernhard Schölkopf Metin Sitti Michael Black Moritz Hardt Christoph Keplinger Katherine J. Kuchenbecker Matthias Tröndle Florian Mayer

Perceiving Systems Talk Tiantian Wang 11-01-2022 Animatable humans from monocular RGB(D) videos We aim to reconstruct animatable humans from monocular RGB(D) videos. Learning user-controlled representation under novel poses remains a challenging problem. To tackle this problem, I will introduce two related methods. First, to reconstruct animatable photo-realistic humans, we integrate observations across frames and encode the appearance at each individual frame by utilizing the human pose and point clouds as the input. In addition, we utilize a temporal transformer to integrate the features of points in the unseen frames and the tracked points in a handful of automatically-selected key... Arjun Chandrasekaran

Perceiving Systems Talk Arianna Rampini 14-12-2021 Discrete inverse spectral geometry for shape analysis Spectral quantities as the eigenvalues of the Laplacian operator are widely used in geometry processing since they provide a very informative summary of the intrinsic geometry of deformable shapes. Typically, the intrinsic properties of shapes are computed from their representation in 3D space and are used to encode compact geometric features, thus adopting a data-reduction principle. On the contrary, this talk focuses on the inverse problem: namely, recovering an extrinsic embedding from a purely intrinsic encoding, like in the classical “hearing the shape of the drum” problem. I will sta... Silvia Zuffi

Perceiving Systems Talk Yajie Zhao 10-12-2021 Next Generation Lifelike Avatar Creation High-fidelity avatar creation for films and games is tied with complex capture equipment, massive data, a long production cycle, and intensive manual labor by a production team. And it may still be in the notorious Uncanny Valley. In this talk, we will explore how to produce a lifelike avatar in a low-cost way. We will show how to leverage deep learning networks to accelerate and simplify the industrial avatar production procedure from data capturing to animation. And bring photorealism to the next level! Timo Bolkart

Empirical Inference Event 08-12-2021 NeurIPS 2021 Meetup @MPI-IS After almost 2 years of virtual conferences and with little in-person interaction we are happy to announce that the Empirical Inference Department at MPI-IS Tübingen will host an official NeurIPS 2021 Meetup as an in-person event at our institute. Annika Buchholz Maximilian Dax Heiner Kremer Lars Lorch Yucen Luo Bernhard Schölkopf

Haptic Intelligence Talk Arnaud Allemang--Trivalle 07-12-2021 Trimanipulation: Virtual reality training platform Supernumerary robotic limbs could significantly impact human capabilities, offering people to achieve actions that are not possible with only two natural hands. However, as three-hand control is not typical in everyday activities, it is currently unknown how to train people to acquire this "super" capability. In this talk, I will present a virtual reality trimanual platform that I developed during my master's thesis. This system offers to control three virtual hands separately or together in three degrees of freedom. The dominant foot served as the additional source of motor commands for t... Katherine J. Kuchenbecker

Haptic Intelligence Talk David Gueorguiev 25-11-2021 Vibrotactile Patterns for Haptic Surfaces I will explore several rendering solutions for providing rich haptic feedback on surfaces. The main topics will be potential physical barriers to propagation of vibrations in the tactile range, rendering of real-life haptic interactions such as virtual musical instruments, and the potential use of haptic illusions for navigation aids. Katherine J. Kuchenbecker

Haptic Intelligence IS Colloquium Wenzhen Yuan 09-11-2021 Simulating the GelSight Sensors: From Physics to Data In recent years, vision-based high-resolution tactile sensors such as GelSight have been widely used because the rich signal provides useful information regarding the state of the robot and the environment. However, a major barrier for applying tactile sensors like GelSight is the cost. To make the tactile sensors more accessible to a broader community, we propose to build a simulation model for vision-based tactile sensors like GelSight. We explore two modeling methods for making the model: a physically-based method that uses rendering technologies to simulate the sensor's optical design a... Katherine J. Kuchenbecker

Talk Prof. Guoqiang Bi 11-10-2021 Visualizing the multi-scale complexity of the brain.

Perceiving Systems Talk Yandong Wen 05-10-2021 Toward Reconstructing Face from Voice We address a new challenge posed by voice profiling - reconstructing someone’s face from their voice. Specifically, given an audio clip spoken by an unseen person, we aim to reconstruct a face that has as many associations as possible with the speaker in terms of identity. In this talk, I will introduce how we explore and approach the ultimate goal step by step. First, we investigate the audio-visual association by matching voices to faces based on identity, and vice versa. Second, we set up a baseline for reconstructing 2D face images from a voice recording and show reasonable reconstructi... Timo Bolkart

Event 30-09-2021 Anniversary: 10 years MPI-IS & 100 years MPI-MF The Max Planck Institute for Intelligent Systems in Stuttgart and Tübingen is celebrating a double anniversary this year: As one of the oldest and largest institutes of the Max Planck Society, the Max Planck Institute for Metals Research celebrates its 100th anniversary. Simultaneously, we are also celebrating the 10th anniversary of the Max Planck Institute for Intelligent Systems, which emerged from the scientific realignment of the institute in 2011. <p class="p-text-lg">Please join us in celebrating this historic event for our institute!</p> Bernhard Schölkopf Matthias Tröndle Barbara Kettemann Oliwia Gust Claudia Daefler Alejandro Posada Nassim Taghipour Katherine J. Kuchenbecker Gisela Schütz

Perceiving Systems Talk Yuxiang Zhang and Yang Zheng 28-09-2021 DeepMultiCap & Lightweight Multi-person Total Motion Capture Using Sparse Multi-view Cameras We propose DeepMultiCap, a novel method for multi-person performance capture using sparse multi-view cameras. Our method can capture time varying surface details without the need of using pre-scanned template models. To tackle the serious occlusion challenge for close interacting scenes, we combine a recently proposed pixel-aligned implicit function with a parametric model for robust reconstruction of the invisible surface areas. An effective attention-aware module is designed to obtain the fine-grained geometry details from multi-view images, where high-fidelity results can be generated. I... Chun-Hao Paul Huang

Perceiving Systems Talk Meng-Yu Jennifer Kuo 27-09-2021 Refraction and Absorption for Underwater Shape Recovery In this talk the speaker will present her work on the recovery of rigid and deformable 3D shape from underwater images. Silvia Zuffi

Talk Prof. Shahd Safarani and Fabian Sinz 27-09-2021 Towards a robust vision by multi-task learning on monkey visual cortex.

Haptic Intelligence Talk Carlo Sferrazza 24-09-2021 Data-driven, Vision-based Tactile Sensing: Design, Simulation, and Applications to Robot Control Katherine J. Kuchenbecker

Perceiving Systems Talk Tianye Li 23-09-2021 Topologically Consistent Multi-View Face Inference Using Volumetric Sampling High-fidelity face digitization solutions often combine multi-view stereo (MVS) techniques for 3D reconstruction and a non-rigid registration step to establish dense correspondence across identities and expressions. A common problem is the need for manual clean-up after the MVS step, as 3D scans are typically affected by noise and outliers and contain hairy surface regions that need to be cleaned up by artists. Furthermore, mesh registration tends to fail for extreme facial expressions. Most learning-based methods use an underlying 3D morphable model (3DMM) to ensure robustness, but this li... Timo Bolkart

Perceiving Systems Talk Siwei Zhang 22-09-2021 Learning motion priors for 4D human body capture in 3D scenes It is challenging to recover realistic human-scene interactions and high-quality human motions while dealing with occlusions and partial views with a monocular RGB(D) camera. We address this problem by learning motion smoothness and infilling priors from the large scale mocap dataset AMASS, to reduce the jitters, and handle contacts and occlusions, respectively. Furthermore, we combine them into a multi-stage optimization pipeline for the high quality 4D human capture in complex 3D scenes. Chun-Hao Paul Huang

Talk Prof. Cavanagh, Patrick 13-09-2021 The role of motion in localizing objects

Perceiving Systems Talk Bharat Lal Bhatnagar 09-09-2021 Hybrid surface representations: Leveraging implicit functions and parametric models for 3D human modelling Representing 3D humans with parametric body models (eg: SMPL) allows us to control the 3D appearance of a human with explicit parameters for pose, shape and even clothing (to an extent). Implicit function based representations on the other hand, typically lack such interpretable control but can produce more detailed models as compared to parametric approaches. They also are not constrained by topology and resolution. In this talk I would like to discuss how we can combine these two directions and leverage the best of both worlds to model detailed and controllable 3D humans. I will primari... Ahmed Osman Arjun Chandrasekaran

Perceiving Systems Talk Jiefeng Li 06-09-2021 From skeleton to body: Keypoint Estimation is Helpful for Human Body Reconstruction My works mainly lie in inferring human structures from RGB inputs, which starts from 2D keypoint estimation, towards more complex tasks like 3D skeleton inference and SMPL-based human pose & shape estimation. Along this road, we find that high-level tasks, like human body estimation, can benefit a lot from low-level inferred structures, like 3D skeletons, and vice versa. Furthermore, in our latest work, "Human Pose Regression with Residual Log-likelihood Estimation", we unified all the above HPS tasks in a direct regression paradigm, replacing generally accepted heatmap without loss of accu... Yuliang Xiu

Haptic Intelligence PhD Thesis Defense 12-08-2021 HuggieBot: An Interactive Hugging Robot with Visual and Haptic Perception Hugs are one of the first forms of contact and affection humans experience. Receiving a hug is one of the best ways to feel socially supported, and the lack of social touch can have severe adverse effects on an individual's well-being. Due to the prevalence and health benefits of hugging, roboticists are interested in creating robots that can hug humans as seamlessly as humans hug other humans. However, hugs are complex affective interactions that need to adapt to the height, body shape, and preferences of the hugging partner, and they often include intra-hug gestures like squeezes. This di... Alexis Block Katherine J. Kuchenbecker

Perceiving Systems Talk Davis Rempe 27-07-2021 Modeling 3D Human Motion for Improved Pose Estimation Though substantial progress has been made in estimating 3D human poses from dynamic observations, recent methods still struggle to recover physically-plausible motions, and the presence of noise and occlusions remains challenging. In this talk, I'll introduce two methods that tackle these issues by leveraging models of 3D human motion - one physics-based and one learned. In the first approach, an initial 3D motion is refined using a physics-based trajectory optimization that leverages automatically-detected foot contacts from RGB video. In the second, a learned generative model is used as a... Muhammed Kocabas

Perceiving Systems Talk Hao Li 26-07-2021 AI SYNTHESIS: FROM AVATARS TO 3D SCENES In this talk I will motivate how digital humans will impact the future of communication, human-machine interaction, and content creation. I will present our latest 3D avatar digitization technology from Pinscreen from a single photo, and give a live demonstration. I will also showcase how we use hybrid CG and neural rendering solutions for real-time applications used in next generation virtual assistant and virtual production pipelines. I will then present a real-time teleportation system that only uses a single webcam as input, and our latest efforts at UC Berkeley in real-time AI synthesi... Yao Feng

Event 22-07-2021 2021 Ph.D. Graduation Ceremony With this Graduation Ceremony, we celebrate the success of 21 young researchers who successfully defended their doctoral theses during the past 12 months. Six world-class universities are awarding doctoral degrees to this year’s batch of graduating students, who are affiliated either directly with MPI-IS or indirectly through our doctoral programs (Cam-Tue, CLS, CMU, and IMPRS-IS). Cäcilia Heinisch Sarah Danes Sara Sorce

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. 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

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