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Motion prediction is a classic problem in computer vision, which aims at forecasting future motion given the observed pose sequence. Various deep learning models have been proposed, achieving state-of-the-art performance on motion…

Computer Vision and Pattern Recognition · Computer Science 2022-01-10 Pengxiang Su , Zhenguang Liu , Shuang Wu , Lei Zhu , Yifang Yin , Xuanjing Shen

The accurate visual tracking of a moving object is a human fundamental skill that allows to reduce the relative slip and instability of the object's image on the retina, thus granting a stable, high-quality vision. In order to optimize…

Neurons and Cognition · Quantitative Biology 2016-11-24 Anna Montagnini , Laurent Perrinet , Guillaume S Masson

The social-force model is systematically modified to achieve a satisfying agreement with the fundamental diagram. Furthermore, our modification allows an efficient computation of the simulation. Finally, different simulation-results will be…

Physics and Society · Physics 2008-06-27 Mohcine Chraibi , Armin Seyfried

In this paper I explain the reasons that led me to research and conceive a novel technology for dependency parsing, mixing together the strengths of data-driven transition-based and constraint-based approaches. In particular I highlight the…

Computation and Language · Computer Science 2015-07-22 Matteo Grella

Cells and organisms follow aligned structures in their environment, a process that can generate persistent migration paths. Kinetic transport equations are a popular modelling tool for describing biological movements at the mesoscopic…

Cell Behavior · Quantitative Biology 2021-01-13 Nadia Loy , Thomas Hillen , Kevin John Painter

When predicting trajectories of road agents, motion predictors usually approximate the future distribution by a limited number of samples. This constraint requires the predictors to generate samples that best support the task given task…

Robotics · Computer Science 2022-05-27 Xin Huang , Guy Rosman , Ashkan Jasour , Stephen G. McGill , John J. Leonard , Brian C. Williams

Time evolution of quantum systems is accelerated by the fast-forward scaling. We reformulate the method to study systems in a finite-dimensional Hilbert space. For several simple systems, we explicitly construct the acceleration potential.…

Quantum Physics · Physics 2014-04-24 Kazutaka Takahashi

By reanalysing transverse momentum dependence in the perturbative calculation of pion form factor an improved expression of pion form factor which takes into account the transverse momentum dependenc in hard scattering amplitude and…

High Energy Physics - Phenomenology · Physics 2009-10-30 Fu-Guang Cao , Tao Huang

Active systems are inherently out of equilibrium, as they collect energy from their surroundings and transform it into directed motion. A recent theoretical study suggests that binary mixtures of active particles with distinct effective…

Soft Condensed Matter · Physics 2017-11-22 Sunita Kumari , Andre S. Nunes , Nuno A. M. Araujo , Margarida Telo da Gama

The design of adaptive structures is one method to improve sustainability of buildings. Adaptive structures are able to adapt to different loading and environmental conditions or to changing requirements by either small or large shape…

Computational Engineering, Finance, and Science · Computer Science 2020-12-08 Renate Sachse , Florian Geiger , Manfred Bischoff

Everyday locomotion is a complex sensorimotor process that can unfold over multiple timescales, from long-term path planning to rapid, reactive adjustments. However, we lack an understanding of how factors such as environmental demands, or…

Machine Learning · Computer Science 2025-08-28 Wei-Chen Wang , Antoine De Comite , Alexandra Voloshina , Monica Daley , Nidhi Seethapathi

Multi-modal fusion is a basic task of autonomous driving system perception, which has attracted many scholars' interest in recent years. The current multi-modal fusion methods mainly focus on camera data and LiDAR data, but pay little…

Robotics · Computer Science 2022-11-14 Yan Gong , Jianli Lu , Jiayi Wu , Wenzhuo Liu

Traditional foundation models are pre-trained on broad datasets to reduce the training resources (e.g., time, energy, labeled samples) needed for fine-tuning a wide range of downstream tasks. However, traditional foundation models struggle…

Machine Learning · Computer Science 2025-04-24 Majid Farhadloo , Arun Sharma , Mingzhou Yang , Bharat Jayaprakash , William Northrop , Shashi Shekhar

System identification, also known as learning forward models, transfer functions, system dynamics, etc., has a long tradition both in science and engineering in different fields. Particularly, it is a recurring theme in Reinforcement…

What happens if one pushes a cup sitting on a table toward the edge of the table? How about pushing a desk against a wall? In this paper, we study the problem of understanding the movements of objects as a result of applying external forces…

Computer Vision and Pattern Recognition · Computer Science 2016-03-18 Roozbeh Mottaghi , Mohammad Rastegari , Abhinav Gupta , Ali Farhadi

Maintenance scheduling is a complex decision-making problem in the production domain, where a number of maintenance tasks and resources has to be assigned and scheduled to production entities in order to prevent unplanned production…

Machine Learning · Computer Science 2021-08-30 Raphael Lamprecht , Ferdinand Wurst , Marco F. Huber

Legged locomotion holds the premise of universal mobility, a critical capability for many real-world robotic applications. Both model-based and learning-based approaches have advanced the field of legged locomotion in the past three…

Robotics · Computer Science 2024-11-26 Sehoon Ha , Joonho Lee , Michiel van de Panne , Zhaoming Xie , Wenhao Yu , Majid Khadiv

We address the problem of efficiently evaluating target functional dependencies (fds) in the Data Exchange (DE) process. Target fds naturally occur in many DE scenarios, including the ones in Life Sciences in which multiple source relations…

Databases · Computer Science 2016-04-19 Angela Bonifati , Ioana Ileana , Michele Linardi

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of…

Robotics · Computer Science 2020-07-27 Andrey Rudenko , Luigi Palmieri , Michael Herman , Kris M. Kitani , Dariu M. Gavrila , Kai O. Arras

This paper studies stabilizer design for position-controlled humanoid robots. Stabilizers are an essential part for position-controlled humanoids, whose primary objective is to adjust the control input sent to the robot to assist the…

Robotics · Computer Science 2021-08-17 Shunpeng Yang , Hua Chen , Zhen Fu , Wei Zhang