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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[edit]

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 Spring 2015[edit]

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

Date Speaker Title
February 19 Bharat Singh PSPGC: Part-Based Seeds for Parametric Graph-Cuts
February 26 Jingjing Zheng TBD
March 5 Yezhou Yang TBD
March 12 Bahadir (Tentative) TBD
March 19 Spring Break, no meeting
March 26 Sravanthi and Varun M TBD
April 2 Jonghyun (?) or Joe (?) TBD
April 9 Ang (?) Ching-hui (?) TBD
April 16 ICCV deadline, no meeting
April 23 Post ICCV deadline, no meeting
April 30 Aleksandr (?) TBD
May 7 Francisco (?) TBD
May 14 Final Exam, no meeting

Talk Abstracts Spring 2015[edit]

PSPGC: Part-Based Seeds for Parametric Graph-Cuts[edit]

Speaker: Bharat Singh -- Date: Feburary 19, 2015

Abstract: PSPGC is a detection-based parametric graph-cut method for accurate image segmentation. Experiments show that seed positioning plays an important role in graph-cut based methods, so, we propose three seed generation strategies which incorporate information about location and color of object parts, along with size and shape. Combined with low-level regular grid seeds, PSPGC can leverage both low-level and high-level cues about objects present in the image. Multiple-parametric graph-cuts using these seeding strategies are solved to obtain a pool of segments, which have a high rate of producing the ground truth segments. Experiments on the challenging PASCAL2010 and 2012 segmentation datasets show that the accuracy of the segmentation hypotheses generated by PSPGC outperforms other state-of-the-art methods when measured by three different metrics(average overlap, recall and covering) by up to 3.5%. We also obtain the best average overlap score in 15 out of 20 categories on PASCAL2010. Further, we provide a quantitative evaluation of the efficacy of each seed generation strategy introduced.

Past Semesters[edit]

Funded By[edit]

Current Seminar Series Coordinators[edit]

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)

Gone but not forgotten.

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