Your search returned the following 16 documents:

16. Occlusion Patterns for Object Class Detection
    Bojan Pepikj, Michael Stark, Peter Gehler, and Bernt Schiele
    In: IEEE Conference on Computer Vision and Pattern Recognition, oregon convention center, Portland, Oregon, USA, 2014
    
15. Detailed 3D Representations for Object Recognition and Modeling
    Zeeshan Zia, Michael Stark, Bernt Schiele, and Konrad Schindler
    IEEE Transactions on Pattern Analysis and Machine Intelligence , 2013
    
14. Explicit Occlusion Modeling for 3D Object Class Representations
    Zeeshan Zia, Michael Stark, and Konrad Schindler
    In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Portland, Oregon, 2013
    
13. Occlusion Patterns for Object Class Detection
    Bojan Pepik, Michael Stark, Peter Gehler, and Bernt Schiele
    In: Computer Vision - CVPR 2013 : Computer Vision and Pattern Recognition, Oregon Convention Center, Portland, Oregon, USA, 2013
    
12. Combining Language Sources and Robust Semantic Relatedness for Attribute-Based Knowledge Transfer
    Marcus Rohrbach, Michael Stark, György Szarvas, and Bernt Schiele
    In: Trends and Topics in Computer Vision : ECCV 2010 Workshops, Heraklion, Crete, Greece, 2012, 15-28
    
11. Fine-grained categorization for 3D scene understanding
    Michael Stark, Jonathan Krause, Bojan Pepik, David Meger, James J. Little, Bernt Schiele, and Daphne Koller
    In: British Machine Vision Conference (BMVC) 2012, Surrey, UK, 2012, 36.1-36.12, paper no. 36.
    
10. Teaching 3D Geometry to Deformable Part Models
    Bojan Pepik, Michael Stark, Peter Gehler, and Bernt Schiele
    In: 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, United States, 2012, 3362-3369
    
9. What Makes a Good Detector? - Structured Priors for Learning from Few Examples
   Tianshi Gao, Michael Stark, and Daphne Koller
   In: Computer Vision - ECCV 2012 : 12th European Conference on Computer Vision, Florence, Italy, 2012, 354-367
   
8. 3D2PM - 3D Deformable Part Models
   Bojan Pepik, Peter Gehler, Michael Stark, and Bernt Schiele
   In: Computer Vision - ECCV 2012 : 12th European Conference on Computer Vision, Firenze, Italy, 2012, 356-370
   
7. Evaluating Knowledge Transfer and Zero-Shot Learning in a Large-Scale Setting
   Marcus Rohrbach, Michael Stark, and Bernt Schiele
   In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs,CO, 2011, 1641-1648
   [PDF: Download: rohrbach11cvpr.pdf]
   
6. Revisiting 3D Geometric Models for Accurate Object Shape and Pose
   M. Zeeshan Zia, Michael Stark, Bernt Schiele, and Konrad Schindler
   In: 2011 IEEE International Conference on Computer Vision : WS08, Workshop on 3D representation and recognition (3dRR-11), Barcelona, Spain, 2011, 569-576. Note: won the 3rd International IEEE Workshop on 3D Representation and Recognition (3dRR-11) best paper award
   
5. Back to the Future: Learning Shape Models from 3D CAD Data
   Michael Stark, Michael Goesele, and Bernt Schiele
   In: 21st British Machine Vision Conference (BMVC), Aberystwyth, Wales, 2010, 106,1-106,11, paper no. 106.
   
4. Categorical Perception
   Mario Fritz, Andriluka Mykhaylo, Sanja Fidler, Michael Stark, Ales Leonardis, and Bernt Schiele
   In: Cognitive Systems, 2010, 131-164
   
3. Combining Language Sources and Robust Semantic Relatedness for Attribute-Based Knowledge Transfer
   Marcus Rohrbach, Michael Stark, György Szarvas, and Bernt Schiele
   In: First International Workshop on Parts and Attributes in conjunction with ECCV 2010, Crete, Greece, 2010
   [PDF: Download: rohrbach10eccvw.pdf]
   
2. Multi-Modal Learning
   Danijel Skocaj, Kristan Matej, Alen Vrecko, Ales Leonardis, Mario Fritz, Michael Stark, Bernt Schiele, Somboon Hongeng, and Jeremy L. Wyatt
   In: Cognitive Systems, 2010, 265-309
   
1. What helps Where - and Why? Semantic Relatedness for Knowledge Transfer
   Marcus Rohrbach, Michael Stark, György Szarvas, Iryna Gurevych, and Bernt Schiele
   In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, USA, 2010, 910-917
   [PDF: Download: rohrbach10cvpr.pdf]