VASC Seminar
Arun Ross
Professor
Michigan State University

Biometrics in a Deep Learning World

Newell-Simon Hall 3305

Abstract: Biometrics is the science of recognizing individuals based on their physical and behavioral attributes such as fingerprints, face, iris, voice and gait. The past decade has witnessed tremendous progress in this field, including the deployment of biometric solutions in diverse applications such as border security, national ID cards, amusement parks, access control, and smartphones. [...]

VASC Seminar
Andrea Tagliasacchi
Associate Professor
Simon Fraser University

Neural World Models

Newell-Simon Hall 4305

Abstract: Computer vision researchers have pushed the limits of performance in perception tasks involving natural images to near saturation. With self-supervised inference driven by recent advancements in generative modeling, it can be debated that the era of large image models is coming to a close, ushering in an era focused on video. However, it's worth [...]

RI Seminar
Chien-Ming Huang
John C. Malone Assistant Professor
Department of Computer Science, Johns Hopkins University

Becoming Teammates: Designing Assistive, Collaborative Machines

1305 Newell Simon Hall

Abstract:  The growing power in computing and AI promises a near-term future of human-machine teamwork. In this talk, I will present my research group’s efforts in understanding the complex dynamics of human-machine interaction and designing intelligent machines aimed to assist and collaborate with people. I will focus on 1) tools for onboarding machine teammates and [...]

VASC Seminar
Ce Zheng
Ph.D. candidate at Center for Research in Computer Vision
University of Central Florida

Reconstructing 3D Humans from Visual Data

Newell-Simon Hall 3305

Abstract:  Abstract: Understanding humans in visual content is fundamental for numerous computer vision applications. Extensive research has been conducted in the field of human pose estimation (HPE) to accurately locate joints and construct body representations from images and videos. Expanding on HPE, human mesh recovery (HMR) addresses the more complex task of estimating the 3D pose [...]

VASC Seminar
Zhenglun Kong
Ph.D. in the Department of Electrical and Computer Engineering
Northeastern University

Towards Energy-Efficient Techniques and Applications for Universal AI Implementation

Newell-Simon Hall 3305

Abstract: The rapid advancement of large-scale language and vision models has significantly propelled the AI domain. We now see AI enriching everyday life in numerous ways – from community and shared virtual reality experiences to autonomous vehicles, healthcare innovations, and accessibility technologies, among others. Central to these developments is the real-time implementation of high-quality deep [...]

VASC Seminar
Shengjie Zhu
Ph.D. Student
Michigan State University

Structure-from-Motion Meets Self-supervised Learning

Newell-Simon Hall 3305

Abstract: How to teach machine to perceive 3D world from unlabeled videos? We will present new solution via incorporating Structure-from-Motion (SfM) into self-supervised model learning. Given RGB inputs, deep models learn to regress depth and correspondence. With the two inputs, we introduce a camera localization algorithm that searches for certified global optimal poses. However, the [...]

VASC Seminar
Qi Sun
Assistant Professor
New York University

Toward Human-Centered XR: Bridging Cognition and Computation

Newell-Simon Hall 3305

Abstract:   Virtual and Augmented Reality enables unprecedented possibilities for displaying virtual content, sensing physical surroundings, and tracking human behaviors with high fidelity. However, we still haven't created "superhumans" who can outperform what we are in physical reality, nor a "perfect" XR system that delivers infinite battery life or realistic sensation. In this talk, I will discuss some of our [...]

Seminar
C. Karen Liu
Professor
Computer Science Department, Stanford University

Carnegie Mellon Graphics Colloquium: C. Karen Liu : Building Large Models for Human Motion

Rashid Auditorium - 4401 Gates and Hillman Centers

Building Large Models for Human Motion Large generative models for human motion, analogous to ChatGPT for text, will enable human motion synthesis and prediction for a wide range of applications such as character animation, humanoid robots, AR/VR motion tracking, and healthcare. This model would generate diverse, realistic human motions and behaviors, including kinematics and dynamics, [...]

RI Seminar
Dr. Michael Yip
Associate Professor
Dept. of Electrical and Computer Engineering, The University of California San Diego

Teaching a Robot to Perform Surgery: From 3D Image Understanding to Deformable Manipulation

1305 Newell Simon Hall

Abstract: Robot manipulation of rigid household objects and environments has made massive strides in the past few years due to the achievements in computer vision and reinforcement learning communities. One area that has taken off at a slower pace is in manipulating deformable objects. For example, surgical robotics are used today via teleoperation from a [...]

VASC Seminar
Yanxi Liu
Professor
Penn State University

Zeros for Data Science

Newell-Simon Hall 3305

Abstract: The world around us is neither totally regular nor completely random. Our and robots’ reliance on spatiotemporal patterns in daily life cannot be over-stressed, given the fact that most of us can function (perceive, recognize, navigate) effectively in chaotic and previously unseen physical, social and digital worlds. Data science has been promoted and practiced [...]