The PASCAL Visual Object Classes Challenge Workshop 2008

17th October 2008, ECCV 2008, Marseille, France

Introduction

This workshop presented and discussed the results of the PASCAL Visual Object Classes Challenge (VOC2008). As in previous years' challenges there are two main competitions, one testing image classification ("does the image contain an instance of this class?"), and one testing object detection ("provide a bounding box for each instance of the class, if any"). In addition there are two 'taster' competitions: the first evaluates the object layout in more detail ("detect the hands, feet etc for a person"), the second evaluates object segmentation at the pixel level.

A new database has been prepared consisting of 20 classes with around 25000 annotated instances in total. The images are obtained from flickr. The classes include people, cats, dogs, cars, motorbikes, bottles and sofas. The annotation includes a rectangular bounding box and flags to indicate pose and level of difficulty.

Full details of the challenge.

Venue

The workshop was held on the morning of October 17th 2008, in association with ECCV 2008.

Programme

09:00 - 09:25	Overview and results of the classification challenge Mark Everingham University of Leeds [PDF]
09:25 - 10:00	Classification methods SurreyUVA_SRKDA method Muhammad Atif Tahir¹, Koen van de Sande², Jasper Uijlings², Fei Yan¹, Xirong Li², Krystian Mikolajczyk¹, Josef Kittler¹, Theo Gevers², Arnold Smeulders² ¹University of Surrey; ²University of Amsterdam [PDF] [Code] UIUC_CMU method Derek Hoiem¹, Santosh Divvala², James H. Hays² ¹University of Illionois Urbana-Champaign; ²Carnegie Mellon University [PDF]
10:00 - 10:20	Overview and results of the detection challenge Mark Everingham University of Leeds [PDF]
10:20 - 10:55	Detection methods LEAR_PlusClass method Hedi Harzallah, Cordelia Schmid, Frederic Jurie, Adrien Gaidon INRIA Rhone-Alpes [PDF] UoCTTIUCI method Pedro Felzenszwalb¹, Ross Girshick¹, David McAllester², Deva Ramanan³ ¹University of Chicago; ²TTI Chicago; ³University of California, Irvine [PDF] [Code]
10:55 - 11:25	Break
11:25 - 11:40	Overview and results of the segmentation taster challenge John Winn Microsoft Research Cambridge [PDF]
11:40 - 12:15	Segmentation methods XRCE_Seg method Gabriela Csurka, Florent Perronnin, Yan Liu Xerox Research Centre Europe (XRCE), Textual and Visual Pattern Analysis Group [PDF] BrookesMSRC method Lubor Ladicky¹, Phil Torr¹, Pushmeet Kohli² ¹Oxford Brookes University; ²Microsoft Research Cambridge [PDF]
12.15 - 12.30	Conclusions and discussion

Organizers

Mark Everingham (University of Leeds), me@comp.leeds.ac.uk
Luc van Gool (ETHZ, Zurich)
Chris Williams (University of Edinburgh)
John Winn (Microsoft Research Cambridge)
Andrew Zisserman (University of Oxford)

Support

The preparation and running of this challenge is supported by the EU-funded PASCAL Network of Excellence on Pattern Analysis, Statistical Modelling and Computational Learning.