Below is a list of some papers related to the research that we will do in this class. We encourage you to read the papers in the first section as well as those related to your particular project. Additional papers may also be suggested by the course staff or fellow students.

• Scene Understanding
• S. Gould et al., Decomposing a Scene into Geometric and Semantically Consistent Regions, ICCV 2009. [PDF]
• L. Jai-Li et al., Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework, CVPR 2009. [PDF]
• D. Hoiem et al., Closing the loop in scene interpretation, CVPR 2008. [PDF]
• G. Heitz et al., Cascaded classification models: combining models for holistic scene understanding, NIPS 2008. [PDF]
• A. Thomas et al., Depth-From-Recognition: Inferring Meta-data by Cognitive Feedback, 3DRR 2007. [PDF]

• Context
• G. Heitz and D. Koller, Learning Spatial Context: Using Stuff to Find Things. ECCV 2008. [PDF]
• A. Rabinovich et al., Objects in Context. ICCV 2007. [PDF]
• M. Fink and P. Perona, Mutual Boosting for Contextual Inference, NIPS 2003. [PDF]
• A. Torralba, Contextual Priming for Object Detection. IJCV 2001. [PDF]

• Object Detection
• C. Gu, J. Lim, P. Arbelaez and J. Malik, Recognition using Regions, CVPR 2009. [PDF]
• N. Dalal and B. Triggs, Histogram of oriented gradients for human detection, CVPR 2005. [PDF]
• A. Torralba et al., Sharing features: efficient boosting procedures for multiclass object detection, CVRP 2004. [PDF]
• B. Leibe and B. Schiele. Scale Invariant Object Categorization Using a Scale-Adaptive Mean-Shift Search. DAGM 2004. [PDF]
• P. Viola and M. Jones, Robust real-time object detection, IJCV 2001. [PDF]

• Multi-class/Figure-Ground Segmentation
• C. Liu, J. Yuen, and A. Torralba ,Nonparametric Scene Parsing: Label Transfer via Dense Scene Alignment, CVPR 2009. [PDF]
• S. Gould et al. Multi-class segmentation with relative location prior, IJCV 2008. [PDF]
• A. Levin and Y. Weiss. Learning to combine bottom-up and top-down segmentation. ECCV 2006. [PDF]
• J. Shotton et al., TextonBoost: Joint appearance, shape and context modeling for multi-class object recognition and segmentation, ECCV 2006. [PDF]
• J. Winn and J. Shotton. The layout consistent random field for recognizing and segmenting partially occluded objects. CVPR 2006. [PDF]
• J. Winn and N. Jojic. LOCUS: Learning object classes with unsupervised segmentation. ICCV 2005. [PDF]
• X. He et al., Multiscale conditional random fields for image labeling, CVPR 2004. [PDF]

• Scene Categorization
• S. Lazebnik, C. Schmid, and J. Ponce, Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, CVPR 2006. [PDF]
• F. Li and P. Perona, A bayesian hierarchical model for learning natural scene categories, CVPR 2005. [PDF]
• A. Oliva and A. Torralba, Modeling the Shape of the Scene: A Holistic Representation of teh Spatial Envelope. IJCV 2001. [PDF]
• J. Vogel and B. Schiele, A Semantic Typicality Measure for Natural Scene Categorization. DAGM 2004. [PDF]

• Boundary Detection
• J. Canny, A computational approach to edge detection. PAMI 1986. [Library]
• D. Martin and C. Fowlkes and J. Malik, Learning to detect natural image boundaries using local brightness, color, and texture cues. PAMI 2004. [PDF]
• C. Carson and S. Belongie and H. Greenspan and J. Malik, Blobworld: Image segmentation using expectation-maximization and its application to image querying. PAMI 2002. [PDF]

• Surface Orientation
• D. Hoiem et al., Geometric Context from a Single Image, ICCV 2005. [PDF]

• Object Outlining
• G. Heitz and G. Elidan and B. Packer and D. Koller, LOOPS: Localizing Object Outlines using Probabilistic Shape, NIPS 2008 [PDF]
• V. Ferrari and F. Jurie and C. Schmid, Accurate Object Detection with Deformable Shape Models Learnt from Images, CVPR 2007. [PDF]
• M.P. Kumar and P.H.S. Torr and A. Zisserman, OBJ-CUT, CVPR 2005. [PDF]

• 3D Reconstruction
• A. Saxena et al., Make3D: Learning 3D Scene Structure from a Single Still Image, PAMI 2008. [PDF]
• D. Hoiem and A. Efros and M. Hebert, Automatic Photo Pop-up. SIGGRAPH 2005. [PDF]

• Image In-Painting
• N. Komodaisk and G. Tziritas, Image Completion Using Efficient Belief Propagation via Priority Scheduling and Dynamic Pruning, CVPR 2009. [PDF]
• A. Criminisi and P. Perez and K. Toyama, Object Removal by Exemplar-Based Inpatining. CVPR 2003. [PDF]
• A. Levin and A. Zomet and Y. Weiss, Learning how to inpaint from global image statistics. ICCV 2003. [PDF]

• Miscellaneous
• N. Snavely, S.M. Seitz, and R. Szeliski, Photo tourism: Exploring photo collections in 3D, SIGGRAPH 2006.
• D. G. Lowe, Distinctive Image Features from Scale-Invariant Keypoints, IJCV 2004.

Software Resources

• Matlab, C/C++, Java
• OpenCV
• STAIR Vision Library
• Dalal/Triggs HoG object detector
• Berkeley Boundary Detector
• Weka data mining toolkit.