VASC Seminar
Christian Richardt
Research Scientist Lead
Meta Reality Labs Research

High-Fidelity Neural Radiance Fields

3305 Newell-Simon Hall

Abstract: I will present three recent projects that focus on high-fidelity neural radiance fields for walkable VR spaces: VR-NeRF (SIGGRAPH Asia 2023) is an end-to-end system for the high-fidelity capture, model reconstruction, and real-time rendering of walkable spaces in virtual reality using neural radiance fields. To this end, we designed and built a custom multi-camera rig to [...]

VASC Seminar
Saining Xie
Assistant Professor
Courant Institute of Mathematical Sciences, New York University

Building Scalable Visual Intelligence: From Represention to Understanding and Generation

3305 Newell-Simon Hall

Abstract: In this talk, we will dive into our recent work on vision-centric generative AI, focusing on how it helps with understanding and creating visual content like images and videos. We'll cover the latest advances, including multimodal large language models for visual understanding and diffusion transformers for visual generation. We'll explore how these two areas [...]

VASC Seminar
Qitao Zhao
Master's Student
Computer Vision, Carnegie Mellon University

Sparse-view Pose Estimation and Reconstruction via Analysis by Generative Synthesis

3305 Newell-Simon Hall

Abstract:  This talk will present our approach for reconstructing objects from sparse-view images captured in unconstrained environments. In the absence of ground-truth camera poses, we will demonstrate how to utilize estimates from off-the-shelf systems and address two key challenges: refining noisy camera poses in sparse views and effectively handling outlier poses.   Bio:  Qitao is a second-year [...]

VASC Seminar
Vimal Mollyn
PhD Student
Human Computer Interaction Institute, Carnegie Mellon University

EgoTouch: On-Body Touch Input Using AR/VR Headset Cameras

3305 Newell-Simon Hall

Abstract:  In augmented and virtual reality (AR/VR) experiences, a user’s arms and hands can provide a convenient and tactile surface for touch input. Prior work has shown on-body input to have significant speed, accuracy, and ergonomic benefits over in-air interfaces, which are common today. In this work, we demonstrate high accuracy, bare hands (i.e., no special [...]

VASC Seminar
Hyunsung Cho
Ph.D. Student
Human-Computer Interaction Institute (HCII) , Carnegie Mellon University

Auptimize: Optimal Placement of Spatial Audio Cues for Extended Reality

3305 Newell-Simon Hall

Abstract:  Spatial audio in Extended Reality (XR) provides users with better awareness of where virtual elements are placed, and efficiently guides them to events such as notifications, system alerts from different windows, or approaching avatars. Humans, however, are inaccurate in localizing sound cues, especially with multiple sources due to limitations in human auditory perception such as [...]

VASC Seminar
Srinath Sridhar
Assistant Professor
Computer Science, Brown University

Generative Modelling for 3D Multimodal Understanding of Human Physical Interactions

3305 Newell-Simon Hall

Abstract: Generative modelling has been extremely successful in synthesizing text, images, and videos. Can the same machinery also help us better understand how to physically interact with the multimodal 3D world? In this talk, I will introduce some of my group's work in answering this question. I will first discuss how we can enable 2D [...]

VASC Seminar
Dr. Yin Yang
Associate Professor
Kahlert School of Computing, University of Utah

High-resolution cloth simulation in milliseconds: Efficient GPU Cloth Simulation with Non-distance Barriers and Subspace Reuse Interactions

3305 Newell-Simon Hall

Abstract: We show how to push the performance of high-resolution cloth simulation, making the simulation interactive (in milliseconds) for models with one million degrees of freedom (DOFs) while keeping every triangle untangled. The guarantee of being penetration-free is inspired by the interior-point method, which converts the inequality constraints to barrier potentials. Nevertheless, we propose a [...]

VASC Seminar
Jiaqi Ma
Assistant Professor
University of Illinois Urbana-Champaign

Practical Challenges and Recent Advances in Data Attribution

3305 Newell-Simon Hall

Abstract: Data plays an increasingly crucial role in both the performance and the safety of AI models. Data attribution is an emerging family of techniques aimed at quantifying the impact of individual training data points on a model trained on them, which has found data-centric applications such as training data curation, instance-based explanation, and copyright [...]