Data-driven constraint-based motion editing

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Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world. This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR. At the advent of ...

We interact with the world through a body that includes hands and fingers. Likewise, providing an avatar allowing the control of a virtual body with fingers is an important step to improve the user experience in VR. When the user and their avatar skeleton ...

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

Human motion analysis and synthesis is integral to many computer vision applications, from autonomous driving to sports analysis. In this thesis, we address several problems in this domain. First we consider active viewpoint selection for pose estimation w ...

Purpose: To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-enco ...

Megapixel single-photon avalanche diode (SPAD) arrays have been developed recently, opening up the possibility of deploying SPADs as general-purpose passive cameras for photography and computer vision. However, most previous work on SPADs has been limited ...

Does gravity affect decision-making? This question comes into sharp focus as plans for interplanetary human space missions solidify. In the framework of Bayesian brain theories, gravity encapsulates a strong prior, anchoring agents to a reference frame via ...

Integration across space and time is essential for the analysis of motion, low contrast, and many more stimuli. A crucial question is what determines the duration of integration. Based on classical models of decision-making, one might expect that integrati ...

In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers commu ...

Compilers assure that any produced optimized code is semantically equivalent to the original code. However, even "correct" compilers may introduce security bugs as security properties go beyond translation correctness. Security bugs introduced by such corr ...

Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...

Detecting people from 2D images and analyzing their motion in 3D have been long standing computer vision problems central to numerous applications such as autonomous driving and athletic training. Recently, with the availability of large amounts of trainin ...

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

Picking up objects to toss them on a conveyor belt are activities generated on a daily basis in the industry. These tasks are still done largely by humans. This paper proposes a unified motion generator for a bimanual robotic systems that enables two 7 deg ...

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

Many scientific systems are studied using computer codes that simulate the phenomena of interest. Computer simulation enables scientists to study a broad range of possible conditions, generating large quantities of data at a faster rate than the laboratory ...

We introduce the task of action-driven stochastic human motion prediction, which aims to predict multiple plausible future motions given a sequence of action labels and a short motion history. This differs from existing works, which predict motions that ei ...

In this paper we propose an unsupervised feature extraction method to capture temporal information on monocular videos, where we detect and encode subject of interest in each frame and leverage contrastive self-supervised (CSS) learning to extract rich lat ...

Being able to understand how optical forces emerge from the interaction of light with matter is paramount for controlling the motion of nanoparticles as well as powering nanomotors. The purpose of this work is to uncover the physical mechanisms at the orig ...

Data-driven constraint-based motion editing

Chattez avec Graph Search

Aggregating Spatial and Photometric Context for Photometric Stereo

From finger animation to full-body embodiment of avatars with different morphologies and proportions

Real-time Self-contact Retargeting of Avatars down to Finger Level

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Automated Human Motion Analysis and Synthesis

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

Seeing Photons in Color

Microgravity induces overconfidence in perceptual decision-making

Processing load, and not stimulus evidence, determines the duration of unconscious visual feature integration

Beyond Spectral Gap: The Role of the Topology in Decentralized Learning

Silent Bugs Matter: A Study of Compiler-Introduced Security Bugs

An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization

Encoder-Decoder Models for Human Segmentation and Motion Analysis

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Dual-Arm Control for Coordinated Fast Grabbing and Tossing of an Object

Memory of Motion for Initializing Optimization in Robotics

Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells

Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction

Temporal Representation Learning on Monocular Videos for 3D Human Pose Estimation

Explanation of Optical Force and Torque on Nanomotors as the Interplay of Huygens Sources