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Computer Vision Student Seminars

The Computer Vision Student Seminars at the University of Maryland College Park are a student-run series of talks given by current graduate students for current graduate students.

To receive regular information about the Computer Vision Student Seminars, subscribe to our mailing list or our talks list.

Description

The purpose of these talks is to:

• Encourage interaction between computer vision students;
• Provide an opportunity for computer vision students to be aware of and possibly get involved in the research their peers are conducting;
• Provide an opportunity for computer vision students to receive feedback on their current research;
• Provide speaking opportunities for computer vision students.

The guidelines for the format are:

• An hour-long weekly meeting, consisting of one 20-40 minute talk followed by discussion and food.
• The talks are meant to be casual and discussion is encouraged.
• Topics may include current research, past research, general topic presentations, paper summaries and critiques, or anything else beneficial to the computer vision graduate student community.

Schedule Fall 2015

All talks take place on Thursdays at 3:30pm in AVW 3450.

Date	Speaker	Title
December 3	Angjoo Kanazawa	Learning 3D Deformation of Animals from 2D Images
December 10	Xintong Han	Automated Event Retrieval using Web Trained Detectors

Talk Abstracts Spring 2015

Talk title

Angjoo Kanazawa 12/03/2015

Understanding how an animal can deform and articulate is essential for a realistic modification of its 3D model. In this paper, we show that such information can be learned from user-clicked 2D images and a template 3D model of the target animal. We present a volumetric deformation framework that produces a set of new 3D models by deforming a template 3D model according to a set of user-clicked images. Our framework is based on a novel locally-bounded deformation energy, where every local region has its own stiffness value that bounds how much distortion is allowed at that location. We jointly learn the local stiffness bounds as we deform the template 3D mesh to match each user-clicked image. We show that this seemingly complex task can be solved as a sequence of convex optimization problems. We demonstrate the effectiveness of our approach on cats and horses, which are highly deformable and articulated animals. Our framework produces new 3D models of animals that are significantly more plausible than methods without learned stiffness.

paper

Past Semesters

• Spring 2015
• Fall 2014
• Spring 2014
• Fall 2013
• Summer 2013
• Spring 2013
• Fall 2012
• Spring 2012
• Fall 2011
• Summer 2011

Funded By

• Computer Vision Faculty

Current Seminar Series Coordinators

Emails are at umiacs.umd.edu.

Jonghyun Choi, jhchoi@	(student of Professor Larry Davis)
Austin Myers, amyers@	(student of Professor Yiannis Aloimonos)
Angjoo Kanazawa, kanazawa@	(student of Professor David Jacobs)
Ching-Hui Chen, ching@	(student of Professor Rama Chellappa)

Gone but not forgotten.

Raviteja Vemulapalli, raviteja @	(student of Professor Rama Chellappa)
Sameh Khamis
Ejaz Ahmed
Anne Jorstad	now at EPFL
Jie Ni	now at Sony
Sima Taheri
Ching Lik Teo

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