« View All Resources

Special Topics in Computer Vision CS7670, Fall 2011, Cornell University

Computer Vision Central - Posted on May 15, 2012 at 9:00 pm.

  • Links: http://www.cs.cornell.edu/courses/cs7670/2011fa/
  • Details:
  • DateTopicsPapers and linksPresentersItems due
    Aug 26Course intro handout
    Topic preferences due via CMS by Tuesday August 30
    Aug 30No class -- instructor out of town 

    Sep 1No class -- instructor out of town 

    Sep 6Object Detection and Exemplars

    • Ensemble of Exemplar-SVMs for Object Detection and Beyond. Malisiewicz, Gupta, Efros, ICCV 2011. [pdf,code,www]
    • Recognition by association via learning per-exemplar distances. Malisiewicz and Efros, CVPR 2008. [pdf,www]
    • Beyond Categories: The Visual Memex Model for Reasoning About Object Relationships. Malisiewicz and Efros, NIPS 2009. [pdfwww]
    • An exemplar model for learning object classes. Chum and Zisserman, CVPR 2007. [pdf]


    Sep 8Saliency

    • Learning to Predict Where Humans Look. T. Judd, K. Ehinger, F. Durand, A. Torralba. ICCV 2009. [pdfwww]


    I. 3D Geometry
    Sep 13Multi-view Stereo

    Multi-view stereo
    • * Reconstructing Building Interiors from Images. Furukawa, Curless, Seitz, Szeliski  [pdfwww]
    • * Piecewise Planar and Non-Planar Stereo for Urban Scene Reconstruction. Gallup, Frahm, Pollefeys. CVPR 2010.  [pdf,wwwwmv]
    • Manhattan-World Stereo. Furukawa, Curless, Seitz, Szeliski, CVPR 2009. [pdfwww]
    • Piecewise planar stereo for image-based rendering. Sinha, Steedly, Szeliski, ICCV 2009. [pdfwww]


    Sep 15User-Assisted 3D Reconstruction

    User-assisted 3D reconstruction
    • * Interactive 3D Architectural Modeling from Unordered Photo Collections. Sinha, Steedly, Szeliski, Agrawala, Pollefeys, SIGGRAPH Asia 2008. [pdfwww]
    • Active Learning for Piecewise Planar 3D Reconstruction.Kowdle, Chang, Gallagher, Chen, CVPR 2011. [pdfwww]
    • 3D Modeling with Silhouettes. Rivers, Durand, Igarashi. SIGGRAPH 2010. [pdfwww].


    Sep 20New 3D Sensors

    New 3D Sensors

    • * Real-Time Human Pose Recognition in Parts from Single Depth Images. Shotton, et al, CVPR 2011. [pdf]
    • RGB-D Mapping: Using depth cameras for dense 3D modeling of indoor environments. Henry, Krainin, Herbst, Ren, Fox. ISER 2010. [pdfwww]
    • Autonomous Generation of Complete 3D Object Models Using Next Best View Manipulation Planning. Krainin, Curless, Fox, ICRA 2011. [pdf]
    • Kernel Descriptors for Visual Recognition, Bo et al., NIPS 2010. [pdf]
    • A Large-Scale Hierarchical Multi-View RGB-D Object Dataset, Lai et al., ICRA 2011. [pdf,www]


    Project proposals due
    Sep 22Structure from motion

    Structure from motion
    • Semantic Structure from Motion. Bao and Savarese, CVPR 2011. [pdfwww]
    • Building Rome in a Day. Agarwal, Snavely, Simon, Seitz, Szeliski. ICCV 2009.  [pdfwwwcode]
    • Building Rome on a Cloudless Day. Frahm, Georgel, Gallup, Johnson, Raguram, Wu, Jen, Dunn, Clipp, Lazebnik, Pollefeys  [pdfwwwcode]
    • Disambiguating Visual Relations Using Loop Constraints. Zach, Klopschitz, Pollefeys, CVPR 2010. [pdf]


    II. Computational Photography
    Sep 27Computational Photography

    Intrinsic Images and White Balance

    Intrinsic images

    • * Light Mixture Estimation for Spatially Varying White Balance. Hsu, Mertens, Paris, Avidan, Durand. SIGGRAPH 2008. [pdfwww]
    • * User Assisted Intrinsic Images. Bousseau, Paris, Durand, SIGGRAPH Asia 2009. [pdfwww]
    Daniel, Ivo

    [pdf (Daniel),pdf (Ivo)]

    Sep 29Computational Photography

    Fun with Light Transport

    Light Transport

    • * Dual Photography. Sen, Chen, Garg, Marschner, Horowitz, Levoy, Lensch. SIGGRAPH 2005. [pdfwww]
    • Optical Computing for Fast Light Transport Analysis. O'Toole and Kutulakos, SIGGRAPH Asia 2010. [pdfwww]
    • Compressive Light Transport Sensing. Peers, Mahajan, Lamond, Ghosh, Matusik, Ramamoorthi, Debevec, TOG 2009. [pdf,www]
    • Wavelet Environment Matting. Peers, Dutre. EGSR 2003. [pdf,www]
    • Symmetric Photography: Exploiting Data-sparseness in Reflectance Fields. Garg, Talvala, Levoy, Lensch, EGSR 2006. [pdfwww]
    Kevin [pdf]
    Oct 4Illumination


    • * Estimating Natural Illumination from a Single Outdoor Image. Lalonde, Efros, Narasimhan, ICCV 2009. [pdfwww]
    • Detecting Ground Shadows in Outdoor Consumer Photographs. Lalonde, Efros, Narasimhan. ECCV 2010.
    • Single-Image Shadow Detection and Removal using Paired Regions. Guo, Dai, Hoiem, CVPR 2011. [pdfwww]


    III. Image Matching and Retrieval
    Oct 6Large-Scale Image Collections

    Large-Scale Image Collections

    • * Small codes and large databases for recognition. Torralba, Fergus, Weiss, CVPR 2008. [pdfwww]
    • * ImageNet: A Large-Scale Hierarchical Image Database. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li and L. Fei-Fei, CVPR 2009. [pdfwww]
    • Nonparametric scene parsing: Label transfer via dense scene alignment. C. Liu, J. Yuen and A. Torralba. CVPR, 2009. [pdf,www]
    • 80 million tiny images: a large dataset for non-parametric object and scene recognition. Torralba, Fergus, Freeman. PAMI 2008. [pdf]
    • Attribute Learning in Large-scale Datasets. O. Russakovsky and L. Fei-Fei, Proc. ECCV Workshop on Parts and Attributes, 2010. [pdf]
    • What does classifying more than 10,000 image categories tell us? J. Deng, A. Berg, K. Li and L. Fei-Fei, ECCV 2010. [pdf]
    Henry and Yimeng


    Oct 11Fall break -- no classes---
    Oct 13Image Representations

    Image Representations

    • * What You Saw is Not What You Get: Domain Adaptation Using Asymmetric Kernel Transforms. Kulis, Saenko, Darrell, CVPR 2011. [pdf]
    • * Informative Feature Selection for Object Recognition via Sparse PCA. Naikal, Yang, Sastry, ICCV 2011. [pdfwww]
    • Image Retrieval with Geometry Preserving Visual Phrases. Zhang, Jia, Chen, CVPR 2011. [pdf]
    • Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories. Lazebnik, Schmid, Ponce, CVPR 2006. [pdfcodeslides]
    • Video Google: A Text Retrieval Approach to Object Matching in Videos. Sivic and Zisserman, ICCV 2003. 
    • Scalable Recognition with a Vocabulary Tree. Nister and Stewenius, CVPR 2006. [pdfslides]


    Oct 18Instructor out of town -- no class---
    Oct 20Guest Lecture -- Andy Gallagher (Kodak), Dhruv Batra (TTI)
    Oct 25Image Representations (Sparse Coding)

    Sparse coding

    • * Linear Spatial Pyramid Matching Using Sparse Coding for Image Classification. Yang, Yu, Gong, Huang, CVPR 2009. [pdf,www]
    • * Locality-constrained Linear Coding for Image Classification. Wang, Yang, Yu, Lv, Huang, Gong. CVPR 2010. [pdfwww]
    Oct 27Feature Detection and Matching

    Feature Detection and Matching

    • * Edge Foci Interest Points. Zitnick and Ramnath, ICCV 2011. [pdfwww]
    • Boundary-Preserving Dense Local Regions. Kim and Grauman, CVPR 2011. [pdfwww]
    • LDAHash: Improved Matching with Smaller Descriptors. Strecha, Bronstein, Bronstein, Fua, PAMI Submission. [pdfcode,www]
    • Object Recognition from Local Scale-Invariant Features. Lowe, IJCV 2004. [pdf, code, other implementations of SIFT]
    • Local Invariant Feature Detectors: A Survey. Tuytelaars and Mikolajczyk. Foundations and Trends in Computer Graphics and Vision, 2008. [pdf] [Oxford code] [Read pp. 178-188, 216-220, 254-255]
    • SURF: Speeded Up Robust Features. Bay, Ess, Tuytelaars, and Van Gool, CVIU 2008. [pdf] [code]
    • Robust Wide Baseline Stereo from Maximally Stable Extremal Regions. J. Matas, O. Chum, U. Martin, and T. Pajdla, BMVC 2002. [pdf]
    • A Performance Evaluation of Local Descriptors. Mikolajczyk and Schmid, CVPR 2003. [pdf]
    • Oxford group interest point software
    • Andrea Vedaldi's code, including SIFT, MSER, hierarchical k-means.
    • INRIA LEAR team's software, including interest points, shape features

    DanielProject updates due Friday
    Nov 1Machine Learning for Image Matching

    Machine Learning

    • * Fast Keypoint Recognition using Random Ferns. Özuysal, Calonder, Lepetit, Fua, PAMI, March 2010. [pdfwww]
    • * Decision Tree Fields. Nowozin, Rother, Bagon, Yao, Sharp, Kohli, ICCV 2011. [pdf]
    • Descriptor Learning for Efficient Retrieval. Philbin , Isard, Sivic, Zisserman. ECCV 2010. [pdf]
    • Learning a Fine Vocabulary. Mikulık, Perdoch, Chum, Matas. ECCV 2010. [pdf]
    Ian, Song
    IV: Object Recognition and Scene Understanding
    Nov 3Geometric Context

    Geometric Context

    • * Closing the Loop on Scene Interpretation. Hoiem, Efros, and Hebert, CVPR 2008.
    • * Recovering Occlusion Boundaries from a Single Image. Hoiem, Stein, Efros, and Hebert. [pdfwwwcode]
    • Recovering Surface Layout from a Single Image. Hoiem, Efros, and Hebert. [pdfcode]
    • Thinking Inside the Box: Using Appearance Models and Context Based on Room Geometry. Hedau, Hoiem, Forsyth, ECCV 2010. [pdf]
    • Recovering the Spatial Layout of Cluttered Rooms. Hedau, Hoiem, Forsyth, ICCV 2009. [pdfcodewww]
    • Segmenting Scenes by Matching Image Composites. Russell, Efros, Sivic, Freeman, Zisserman, NIPS 2009. 
    • Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories. Su, Sun, Li, Savarese, ICCV 2009. [pdf]

    Zhaoyin, Adarsh
    Nov 8Attributes


    • * Describing Objects by their Attributes. Farhadi, Endres, Hoiem, Forsyth, CVPR 2009. [pdfwww]
    • * Relative Attributes. Parikh and Grauman, ICCV 2011. 
    • Attribute-Centric Recognition for Cross-Category Generalization. Farhadi, Endres, Hoiem, CVPR 2010. [pdf]
    Amir, Ruogu
    Nov 10Materials


    • * Inferring Reflectance under Real-world Illumination. Romeiro, Zickler, IJCV. [pdf]
    • * Exploring features in a Bayesian framework for material recognition. Liu, Sharan, Adelson, Rosenholtz, CVPR 2010. [pdf,www]
    • What An Image Reveals About Material Reflectance. Chandraker, Ramamoorthi, ICCV 2011. [pdf]
    Kevin, Chun-Po
    Nov 15No class---
    Nov 17No class---
    Nov 22No class---
    Nov 24Thanksgiving -- no classes---
    Nov 29Event Recognition from Videos

    Event Recognition from Videos

    • * Learning realistic human actions from movies. I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld. In CVPR 2008. [pdf,www]

    • Activity recognition using the velocity histories of tracked keypoints. R. Messing, C. Pal, and H. A. Kautz. ICCV 2009. [pdf,www]
    • Behavior recognition via sparse spatio-temporal features. P. Dollar, V. Rabaud, G. Cottrell, and S. J. Belongie. PETS Workshop, 2005. [pdf]
    • A “string of feature graphs” model for recognition of complex activities in natural videos. U. Gaur, Y. Zhu, B. Song, and A. Roy-Chowdhury. ICCV 2011. [pdf]


    Dec 1Image-to-text and Recognition in social context

    Image to text

    • * Seeing People in Social Context: Recognizing People and Social Relationships. Wang, Gallagher, Luo, and Forsyth. ECCV 2010. [pdf]
    • * Baby Talk: Understanding and Generating Simple Image Descriptions. Kulkarni, Premraj, Dhar, Li, Choi, Berg, and Berg. CVPR 2011. [pdf]
    • Autotagging Facebook: Social Network Context Improves Photo Annotation. Stone, Zickler, Darrell. Workshop on Internet Vision. [pdf]
    • Understanding Images of Groups of People. Gallagher and Chen. CVPR 2009. [pdf]
    • Estimating Age, Gender and Identity using First Name Priors. Gallagher and Chen, CVPR 2008. [www]

    Amir andHenry


    Dec 8

    Final presentations

    k();} ?>