VASC Seminar
Kenneth Marino
Research Scientist
Google DeepMind

World Knowledge in the Time of Large Models

Newell-Simon Hall 3305

Abstract:  This talk will discuss the massive shift that has come about in the vision and ML community as a result of the large pre-trained language and language and vision models such as Flamingo, GPT-4, and other models. We begin by looking at the work on knowledge-based systems in CV and robotics before the large model [...]

VASC Seminar
Shunsuke Saito
Research Scientist
Meta Reality Labs Research

Digital Human Modeling with Light

Newell-Simon Hall 3305

Abstract: Leveraging light in various ways, we can observe and model physical phenomena or states which may not be possible to observe otherwise. In this talk, I will introduce our recent exploration on digital human modeling with different types of light. First, I will present our recent work on the modeling of relightable human heads, [...]

VASC Seminar
Jonathon Luiten
Postdoctoral Fellow
RWTH Aachen and Carnegie Mellon University

Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis

Newell-Simon Hall 3305

Abstract: We present a method that simultaneously addresses the tasks of dynamic scene novel-view synthesis and six degree-of-freedom (6-DOF) tracking of all dense scene elements. We follow an analysis-by-synthesis framework, inspired by recent work that models scenes as a collection of 3D Gaussians which are optimized to reconstruct input images via differentiable rendering. To model [...]

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 [...]

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 [...]

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 [...]

VASC Seminar
Agata Lapedriza
Principal Research Scientist/Professor
Northeastern University

Emotion perception: progress, challenges, and use cases

Newell-Simon Hall 3305

Abstract: One of the challenges Human-Centric AI systems face is understanding human behavior and emotions considering the context in which they take place. For example, current computer vision approaches for recognizing human emotions usually focus on facial movements and often ignore the context in which the facial movements take place. In this presentation, I will [...]