How Good are Local Features for Classes of Geometric Objects. - Michael Stark 003; Bernt Schiele (ICCV, 2007)

XQuery Streaming à la Carte. - Mary F. Fernández; Philippe Michiels; Jérôme Siméon; Michael Stark 003 (ICDE, 2007)

Functional Object Class Detection Based on Learned Affordance Cues. - Michael Stark 003; Philipp Lies; Michael Zillich; Jeremy L. Wyatt; Bernt Schiele (ICVS, 2008)

A shape-based object class model for knowledge transfer. - Michael Stark 003; Michael Goesele; Bernt Schiele (ICCV, 2009)

Shading cues for object class detection. - Michael Stark 003; Michael Goesele; Bernt Schiele (ICCV Workshops, 2009)

Categorical Perception. - Mario Fritz; Mykhaylo Andriluka; Sanja Fidler; Michael Stark 003; Ales Leonardis; Bernt Schiele (Cognitive Systems, 2010)

Multi-modal Learning. - Danijel Skocaj; Matej Kristan; Alen Vrecko; Ales Leonardis; Mario Fritz; Michael Stark 003; Bernt Schiele; Somboon Hongeng; Jeremy L. Wyatt (Cognitive Systems, 2010)

Back to the Future: Learning Shape Models from 3D CAD Data. - Michael Stark 003; Michael Goesele; Bernt Schiele (BMVC, 2010)

What helps where - and why? Semantic relatedness for knowledge transfer. - Marcus Rohrbach; Michael Stark 003; György Szarvas; Iryna Gurevych; Bernt Schiele (CVPR, 2010)

Combining Language Sources and Robust Semantic Relatedness for Attribute-Based Knowledge Transfer. - Marcus Rohrbach; Michael Stark 003; György Szarvas; Bernt Schiele (ECCV Workshops (1), 2010)

On knowledge transfer in object class recognition. - Michael Stark 003 (2010)

Evaluating knowledge transfer and zero-shot learning in a large-scale setting. - Marcus Rohrbach; Michael Stark 003; Bernt Schiele (CVPR, 2011)

Revisiting 3D geometric models for accurate object shape and pose. - M. Zeeshan Zia; Michael Stark 003; Bernt Schiele; Konrad Schindler (ICCV Workshops, 2011)

Fine-Grained Categorization for 3D Scene Understanding. - Michael Stark 003; Jonathan Krause; Bojan Pepik; David Meger; James J. Little; Bernt Schiele; Daphne Koller (BMVC, 2012)

Teaching 3D geometry to deformable part models. - Bojan Pepik; Michael Stark 003; Peter V. Gehler; Bernt Schiele (CVPR, 2012)

What Makes a Good Detector? - Structured Priors for Learning from Few Examples. - Tianshi Gao; Michael Stark 003; Daphne Koller (ECCV (5), 2012)

3D2PM - 3D Deformable Part Models. - Bojan Pepik; Peter V. Gehler; Michael Stark 003; Bernt Schiele (ECCV (6), 2012)

Occlusion Patterns for Object Class Detection. - Bojan Pepik; Michael Stark 003; Peter V. Gehler; Bernt Schiele (CVPR, 2013)

Explicit Occlusion Modeling for 3D Object Class Representations. - M. Zeeshan Zia; Michael Stark 003; Konrad Schindler (CVPR, 2013)

3D Object Representations for Fine-Grained Categorization. - Jonathan Krause; Michael Stark 003; Jia Deng 001; Li Fei-Fei 001 (ICCV Workshops, 2013)

Detailed 3D Representations for Object Recognition and Modeling. - M. Zeeshan Zia; Michael Stark 003; Bernt Schiele; Konrad Schindler (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

Are Cars Just 3D Boxes? Jointly Estimating the 3D Shape of Multiple Objects. - Muhammad Zeeshan Zia; Michael Stark 003; Konrad Schindler (CVPR, 2014)

Multi-View Priors for Learning Detectors from Sparse Viewpoint Data. - Bojan Pepik; Michael Stark 003; Peter V. Gehler; Bernt Schiele (ICLR (Poster), 2014)

Enriching object detection with 2D-3D registration and continuous viewpoint estimation. - Christopher Bongsoo Choy; Michael Stark 003; Sam Corbett-Davies; Silvio Savarese (CVPR, 2015)

Image retrieval using scene graphs. - Justin Johnson 001; Ranjay Krishna; Michael Stark 003; Li-Jia Li 001; David A. Shamma; Michael S. Bernstein; Li Fei-Fei 001 (CVPR, 2015)

3D object class detection in the wild. - Bojan Pepik; Michael Stark 003; Peter V. Gehler; Tobias Ritschel 001; Bernt Schiele (CVPR Workshops, 2015)

Towards Scene Understanding with Detailed 3D Object Representations. - M. Zeeshan Zia; Michael Stark 003; Konrad Schindler (Int. J. Comput. Vis., 2015)

Multi-View and 3D Deformable Part Models. - Bojan Pepik; Michael Stark 003; Peter V. Gehler; Bernt Schiele (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Leveraging the Wisdom of the Crowd for Fine-Grained Recognition. - Jia Deng 001; Jonathan Krause; Michael Stark 003; Li Fei-Fei 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Visual Object Class Recognition. - Michael Stark 003; Bernt Schiele; Ales Leonardis (Springer Handbook of Robotics, 2nd Ed., 2016)

Teaching Compositionality to CNNs. - Austin Stone; Hua-Yan Wang; Michael Stark 003; Yi Liu 055; D. Scott Phoenix; Dileep George (CVPR, 2017)

Behavior Is Everything: Towards Representing Concepts with Sensorimotor Contingencies. - Nicholas Hay; Michael Stark 003; Alexander Schlegel; Carter Wendelken; Dennis Park; Eric Purdy; Tom Silver; D. Scott Phoenix; Dileep George (AAAI, 2018)

RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches. - Priya Sundaresan; Quan Vuong; Jiayuan Gu; Peng Xu 010; Ted Xiao; Sean Kirmani; Tianhe Yu; Michael Stark 003; Ajinkya Jain; Karol Hausman; Dorsa Sadigh; Jeannette Bohg; et al. (CoRL, 2024)

Towards Co-Evaluation of Cameras, HDR, and Algorithms for Industrial-Grade 6DoF Pose Estimation. - Agastya Kalra; Guy Stoppi; Dmitrii Marin; Vage Taamazyan; Aarrushi Shandilya; Rishav Agarwal; Anton Boykov; Tze Hao Chong; Michael Stark 003 (CVPR, 2024)

GenCHiP: Generating Robot Policy Code for High-Precision and Contact-Rich Manipulation Tasks. - Kaylee Burns; Ajinkya Jain; Keegan Go; Fei Xia 002; Michael Stark 003; Stefan Schaal; Karol Hausman (IROS, 2024)