VASC Seminar
Wei-Chiu Ma
PhD Candidate
MIT

Mental models for 3D modeling and generation

Newell-Simon Hall 3305

Abstract:  Humans have extraordinary capabilities of comprehending and reasoning about our 3D visual world. One particular reason is that when looking at an object or a scene, not only can we see the visible surface, but we can also hallucinate the invisible parts - the amodal structure, appearance, affordance, etc. We have accumulated thousands of [...]

VASC Seminar
Michael Zollhoefer
Research Scientist
Reality Labs Research

Complete Codec Telepresence

Newell-Simon Hall 3305

Abstract:  Imagine two people, each of them within their own home, being able to communicate and interact virtually with each other as if they are both present in the same shared physical space. Enabling such an experience, i.e., building a telepresence system that is indistinguishable from reality, is one of the goals of Reality Labs [...]

VASC Seminar
Kayvon Fatahalian
Associate Professor of Computer Science
Stanford University

R.I.P ohyay: experiences building online virtual experiences during the pandemic: what works, what hasn’t, and what we need in the future

Newell-Simon Hall 3305

Abstract:  During the pandemic I helped design ohyay (https://ohyay.co), a creative tool for making and hosting highly customized video-based virtual events. Since Fall 2020 I have personally designed many online events: ranging from classroom activities (lectures, small group work, poster sessions, technical papers PC meetings), to conferences, to virtual offices, to holiday parties involving 100's [...]

VASC Seminar
Fabio Pizzati
PhD student
Inria

Physics-informed image translation

Abstract:  Generative Adversarial Networks (GANs) have shown remarkable performances in image translation, being able to map source input images to target domains (e.g. from male to female, day to night, etc.). However, their performances may be limited by insufficient supervision, which may be challenging to obtain. In this talk, I will present our recent works [...]

VASC Seminar
Adriana Kovashka
Associate Professor in Computer Science
University of Pittsburgh

Weak Multi-modal Supervision for Object Detection and Persuasive Media

Newell-Simon Hall 3305

Abstract:  The diversity of visual content available on the web presents new challenges and opportunities for computer vision models. In this talk, I present our work on learning object detection models from potentially noisy multi-modal data, retrieving complementary content across modalities, transferring reasoning models across dataset boundaries, and recognizing objects in non-photorealistic media.  While the [...]

VASC Seminar
Andrew Owens
Assistant Professor
Electrical Engineering & Computer Science , University of Michigan

Learning Visual, Audio, and Cross-Modal Correspondences

Newell-Simon Hall 3305

Abstract:  Today's machine perception systems rely heavily on supervision provided by humans, such as labels and natural language. I will talk about our efforts to make systems that, instead, learn from two ubiquitous sources of unlabeled data: visual motion and cross-modal sensory associations. I will begin by discussing our work on creating unified models for [...]

VASC Seminar
Lachlan MacDonald
Postdoc
Australian Institute for Machine Learning, University of Adelaide

Towards a formal theory of deep optimisation

Newell-Simon Hall 3305

Abstract:  Precise understanding of the training of deep neural networks is largely restricted to architectures such as MLPs and cost functions such as the square cost, which is insufficient to cover many practical settings.  In this talk, I will argue for the necessity of a formal theory of deep optimisation.  I will describe such a [...]

VASC Seminar
Christoph Lassner
Senior Research Scientist
Epic Games

Towards Interactive Radiance Fields

Newell-Simon Hall 3305

Abstract:  Over the last years, the fields of computer vision and computer graphics have increasingly converged. Using the exact same processes to model appearance during 3D reconstruction and rendering has shown tremendous benefits, especially when combined with machine learning techniques to model otherwise hard-to-capture or -simulate optical effects. In this talk, I will give an [...]

VASC Seminar
Rika Antonova
Postdoctoral Scholar
Stanford University

Enabling Self-sufficient Robot Learning

3305 Newell-Simon Hall

Abstract:  Autonomous exploration and data-efficient learning are important ingredients for helping machine learning handle the complexity and variety of real-world interactions. In this talk, I will describe methods that provide these ingredients and serve as building blocks for enabling self-sufficient robot learning. First, I will outline a family of methods that facilitate active global exploration. [...]

VASC Seminar
Vasudevan (Vasu) Sundarababu
SVP & Head of Digital Engineering
Centific

How Computer Vision Helps – from Research to Scale

3305 Newell-Simon Hall

Abstract:  Vasudevan (Vasu) Sundarababu, SVP and Head of Digital Engineering, will cover the topic: ‘How Computer Vision Helps – from Research to Scale’. During his time, Vasu will explore how Computer Vision technology can be leveraged in-market today, the key projects he is currently leading that leverage CV, and the end-to-end lifecycle of a CV initiative - [...]