Mundy, J. L. (2006). "Object Recognition in the Geometric Era: a Retrospective." Lecture Notes in Computer Science 4170/2006. [PDF]
M. Fritz, M. Andriluka, S. Fidler, M. Stark, A. Leonardis and B. Schiele (2010) "Categorical Perception" Chapter in Cognitive Systems, Springer Verlag, 2010 [PDF]
AWM Smeulders, DM Chu, R Cucchiara, S Calderara, A Dehghan, M Shah. Visual Tracking: An Experimental Survey. In PAMI 2014. [PDF]
General Algorithms
Fischler, M. A. and R. C. Bolles (1981). "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography." Communications of the ACM. [PDF]
Felzenszwalb, P. and D. P. Huttenlocher (2004). "Efficient Belief Propagation for Early Vision." CVPR. [PDF]
Boykov, Y., Veksler O., et al. (2001). "Fast Approximate Energy Minimization via Graph Cuts." PAMI. [PDF]
Kappes, Jörg H., et al (2015). .A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. IJCV. [PDF]
Light field
Adelson, E. H. and J. R. Bergen (1991). "The Plenoptic Function and the Elements of Early Vision." Computational Models of Visual Processing. [PDF]
Object Recognition
Torralba, A. (2001). "Contextual Priming for Object Detection." IJCV. [PDF]
Viola, P. and M. J. Jones (2004). "Robust Real-Time Face Detection." IJCV. [PDF]
Murase H. & Nayar, S. K (1995). "Visual learning and recognition of 3-d objects from appearance" IJCV [PDF]
P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan, “Object detection with discriminatively trained part-based models,” PAMI 2010 [PDF]
Krizhevsky, A., Sutskever, I. and Hinton, G. E. ImageNet Classification with Deep Convolutional Neural Networks. NIPS 2012 [PDF]
Razavian, Ali S., et al. "CNN features off-the-shelf: an astounding baseline for recognition." Computer Vision and Pattern Recognition Workshops (CVPRW), 2014 IEEE Conference on. IEEE, 2014. [PDF]
Aravindh Mahendran, Andrea Vedaldi. “Understanding Deep Image Representations by Inverting Them”. CVPR 2015. [PDF]
J. Hosang, R. Beneson, P. Dollar, B. Schiele, “What makes for effective detection proposals?” PAMI 2015 [PDF]
Shape
Kass, M., A. Witkin, et al. (1988). "Snakes: Active contour models." IJCV. [PDF]
Belongie, S., J. Malik, et al. (2002). "Shape Matching and Object Recognition Using Shape Contexts." PAMI. [PDF]
Edges / Filters
Barash, D. (2002). "A Fundamental Relationship between Bilateral Filtering, Adaptive Smoothing and the Nonlinear Diffusion Equation." PAMI. [DOI]
P. Arbelaez, M. Maire, et al. (2011) "Contour Detection and Hierarchical Image Segmentation". PAMI. [PDF]
Piotr Dollár and C. Lawrence Zitnick. Fast Edge Detection Using Structured Forests. PAMI 2015
Features / Descriptors / Matching
Lowe, D. G. (2004). "Distinctive Image Features from Scale-Invariant Keypoints." IJCV. [PDF]
Mikolajczyk, K., T. Tuytelaars, et al. (2005). "A Comparison of Affine Region Detectors." IJCV. [PDF]
Video Google: A Text Retrieval Approach to Object Matching in Video. ICCV 2003. [PDF]
Nister, D. and H. Stewenius (2006). "Scalable Recognition with a Vocabulary Tree." CVPR. [PDF]
I. Laptev (2005), "On Space-Time Interest Points"; in International Journal of Computer Vision, vol 64, number 2/3, pp.107-123. [PDF]
S. Lazebnik, C. Schmid, and J. Ponce. “Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories.” CVPR 2006. [PDF]
N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” CVPR 2005 [PDF]
R. Girshick, J. Donahue, T. Darrell, J. Malik. “Region-based Convolutional Networks for Accurate Object Detection and Semantic Segmentation”. PAMI 2015. [PDF]
Tracking and Active Models
Isard, M. and A. Blake (1998). "Condensation - conditional density propagation for visual tracking." IJCV. [PDF]
Comaniciu, D., V. R. Ramesh, et al. (2000). "Real-time tracking of non-rigid objects using mean-shift." CVPR. [PDF]
Cootes, T. F., G. J. Edwards, et al. (1998). "Active appearance models." ECCV. [PDF]
J. Shotton, R. Girshick, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, P. Kohli, A. Criminisi, A. Kipman, and A. Blake, “Efficient human pose estimation from single depth images,” PAMI, 2013 [PDF]
Action Recognition
Bobick, A. and J. W. Davis (2001). "The Recognition of Human Movement Using Temporal Templates." PAMI. [DOI]
Laptev, I., M. Marszarek, et al. (2008). "Learning realistic human actions from movies." CVPR. [PDF]
Wang, H. and Schmid, C. Action Recognition with Improved Trajectories. ICCV, 2013. [PDF]
Poppe, R. A survey on vision-based human action recognition. Image and vision computing, 2010. [PDF]
Karpathy, Andrej, et al. "Large-scale video classification with convolutional neural networks." Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE, 2014.
Structure from Motion
Triggs, B., P. F. McLauchlan, et al. (1999). "Bundle Adjustment - A Modern Synthesis." Vision Algorithms. [PDF]
Pollefeys, M., R. Koch, et al. (1999). "Self-Calibration and Metric Reconstruction in spite of Varying and Unknown Internal Camera Parameters." IJCV. [PDF]
Snavely, N., S. M. Seitz, et al. (2007). "Modeling the world from Internet photo collections." IJCV. [PDF]
Segmentation / Layer extraction
Comaniciu, D. and P. Meer (2002). "Mean Shift: A Robust Approach toward Feature Space Analysis." PAMI. [DOI]
Felzenszwalb, P. and D. P. Huttenlocher (2004). "Efficient Graph-Based Image Segmentation." IJCV. [PDF]
Shi J. and Malik. J. (2000). "Normalized Cuts and Image Segmentation" PAMI [PDF]
Stereo / Optical Flow
Black, M. J. and P. Anandan (1996). "The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow Fields." Computer Vision and Image Understanding. [PDF]
Baker, S., D. Scharstein, et al. (2009). "A Database and Evaluation Methodology for Optical Flow." MSR TechReport. [PDF]
Zabih, V. K. a. R. (2002). "Multi-camera Scene Reconstruction via Graph Cuts." ECCV. [PDF]
Baker, S. and Matthews, I. (2004) “Lucas-Kanade 20 Years On: A Unifying Framework.” IJCV. [PDF]
Scharstein, D. and R. Szeliski (2002). " A taxonomy and evaluation of dense two-frame stereo correspondence algorithms." IJCV. [PDF]
Texture / Image synthesis
Brown, M. and D. G. Lowe (2003). "Recognising Panoramas." ICCV. [PDF]
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Burt, P. J. and E. H. Adelson (1983). "A multiresolution spline with application to image mosaics." ACM Transactions on Graphics. [PDF]
Efros, A. A. and T. K. Leung (1999). "Texture Synthesis by Non-parametric Sampling." ICCV. [PDF]
Kwatra, V., A. Schodl, et al. (2003). "Graphcut Textures: Image and Video Synthesis Using Graph Cuts." SIGGRAPH. [PDF] [WEBSITE]
Hays, J. and A. Efros (2007). "Scene Completion Using Millions of Photographs." SIGGRAPH. [PDF] [WEBSITE]
Color recognition / HDR
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Video
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Vision for Robotics
J. Engel, T. Schöps, and D. Cremers, LSD-SLAM: Large-Scale Direct Monocular SLAM, In European Conference on Computer Vision (ECCV), 2014. [bib] [pdf] [video]
Richard A. Newcombe, Steven J. Lovegrove and Andrew J. Davison, DTAM: Dense Tracking and Mapping in Real-Time, In ICCV, 2011. [pdf] [video]
Deep Learning
Zeiler, Matthew D., and Rob Fergus. "Visualizing and understanding convolutional networks." Computer Vision–ECCV 2014. Springer International Publishing, 2014. 818-833. [PDF]
Simonyan, Karen, and Andrew Zisserman. "Very deep convolutional networks for large-scale image recognition." arXiv preprint arXiv:1409.1556 (2014). [PDF]
