The PASCAL Visual Object Classes Challenge Workshop 2009

3rd October 2009, ICCV 2009, Kyoto, Japan

Introduction

This workshop will present and discuss the results of the PASCAL Visual Object Classes Challenge (VOC2009). The challenge has three main competitions, one testing image classification ("does the image contain an instance of this class?"), one testing object detection ("provide a bounding box for each instance of the class, if any"), and one evaluating object segmentation at the pixel level. In addition there is a single 'taster' competition, evaluating the object layout in more detail ("detect the hands, feet etc for a person").

A new database has been prepared consisting of 20 classes with around 35,000 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 3rd October 2009, in association with ICCV 2009.

Prizes

The following prizes were announced at the workshop:

Classification
Winner:	NEC/UIUC Yihong Gong, Fengjun Lv, Jinjun Wang, Chen Wu, Wei Xu, Jianchao Yang, Kai Yu, Xi Zhou, Thomas Huang NEC Laboratories America; University of Illinois at Urbana-Champaign
Honourable mentions:	UVA/SURREY Koen van de Sande, Fei Yan, Atif Tahir, Jasper Uijlings, Mark Barnard, Hongping Cai, Theo Gevers, Arnold Smeulders, Krystian Mikolajczyk, Josef Kittler University of Amsterdam; University of Surrey CVC Fahad Shahbaz Khan, Joost van de Weijer, Andrew Bagdanov, Noha Elfiky, David Rojas, Marco Pedersoli, Xavier Boix, Pep Gonfaus, Hany salahEldeen, Robert Benavente, Jordi Gonzalez, Maria Vanrell Computer Vision Centre Barcelona
Detection
Joint Winners:	UoC/TTI Chicago Pedro Felzenszwalb, Ross Girshick, David McAllester University of Chicago; Toyota Technological Institute at Chicago Oxford/MSR India Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew Zisserman University of Oxford; Microsoft Research India
Segmentation
Winner:	Bonn Joao Carreira, Fuxin Li, Cristian Sminchisescu University of Bonn
Runner-up:	CVC Xavier Boix, Josep Maria Gonfaus, Fahad Kahn, Joost van de Weijer, Andrew Bagdanov, Marco Pedersoli, Jordi Gonzalez, Joan Serrat Computer Vision Center Barcelona

Programme

09:30 - 09:50	Overview and results of the detection challenge Mark Everingham University of Leeds [PDF]
09:50 - 11:00	Detection and segmentation methods Multiple kernels for object detection (OXFORD_MKL) Andrea Vedaldi¹, Varun Gulshan¹, Manik Varma², Andrew Zisserman¹ ¹University of Oxford; ²Microsoft Research India [PDF] Using poselets for detection and segmentation (BERKELEY_POSELETS) Lubomir Bourdev^1,2, Subhransu Maji¹, Jitendra Malik¹ ¹UC Berkeley; ²Adobe Systems, Inc. [Powerpoint] Discriminatively trained part based models (UoCTTI_LSVM-MDPM) Pedro Felzenszwalb¹, Ross Girshick¹, David McAllester² ¹University of Chicago; ²Toyota Technological Institute at Chicago - to be presented by Deva Ramanan [PDF] Part-based layered shape models for segmentation (UCI_LAYEREDSHAPE) Charless Fowlkes, Sam Hallman, Deva Ramanan, Yi Yang UC Irvine [PDF] NB: This is unpublished work. Please contact the authors if you plan to make use of any of the ideas presented.
11:00 - 11:30	Break
11:30 - 11:50	Overview and results of the classification challenge Mark Everingham University of Leeds [PDF]
11:50 - 12:10	Classification methods Image classification using Gaussian mixture and local coordinate coding (NECUIUC_CLS-DTCT) Yihong Gong¹, Thomas Huang², Fengjun Lv¹, Jingjun Wang¹, Chen Wu⁴, Wei Xu¹, Jianchao Yang², Kai Yu¹, Tong Zhang³, Xi Zhou² ¹NEC Laboratories America; ²University of Illinois at Urbana-Champaign; ³Rutgers University; ⁴Stanford University [PDF] NB: This is unpublished work. Please contact the authors if you plan to make use of any of the ideas presented.
12:10 - 13:50	Lunch
13:50 - 14:10	Overview and results of the segmentation challenge John Winn¹, Mark Everingham² ¹Microsoft Research Cambridge; ²University of Leeds [PDF]
14:10 - 15:10	Segmentation methods Ranking figure-ground hypotheses for object segmentation (BONN_SVM-SEGM) João Carreira, Fuxin Li, Cristian Sminchisescu University of Bonn [PDF] NB: This is unpublished work. Please contact the authors if you plan to make use of any of the ideas presented. Combining local and global bag-of-word representations for semantic segmentation (CVC_HOCRF) Xavier Boix, Josep Maria Gonfaus, Fahad Shahbaz Kahn, Joost van de Weijer, Andrew Bagdanov, Marco Pedersoli, Jordi González, Joan Serrat Computer Vision Center Barcelona [PDF] NB: This is unpublished work. Please contact the authors if you plan to make use of any of the ideas presented. Hierarchical CRF for object class segmentation (BROOKESMSRC_AHCRF) Lubor Ladicky¹, Chris Russell¹, Pushmeet Kohli², Philip H.S. Torr¹ ¹Oxford Brookes University; ²Microsoft Research Cambridge [PDF]
15:10 - 15:30	Conclusions and discussion [PDF]

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 PASCAL2 Network of Excellence on Pattern Analysis, Statistical Modelling and Computational Learning.