A Database and Evaluation Methodology for Optical Flow von Baker, Simon, Scharstein, Daniel, Lewis, J. P., Roth, Stefan, Black, Michael J., Szeliski, Richard

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A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms von Scharstein, Daniel, Szeliski, Richard

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Evaluation of Cost Functions for Stereo Matching von Hirschmuller, H., Scharstein, D.

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Learning Conditional Random Fields for Stereo von Scharstein, D., Pal, C.

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A Database and Evaluation Methodology for Optical Flow von Baker, S., Scharstein, D., Lewis, J.P., Roth, S., Black, M.J., Szeliski, R.

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A Comparative Study of Energy Minimization Methods for Markov Random Fields von Szeliski, Richard, Zabih, Ramin, Scharstein, Daniel, Veksler, Olga, Kolmogorov, Vladimir, Agarwala, Aseem, Tappen, Marshall, Rother, Carsten

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On Learning Conditional Random Fields for Stereo von Pal, Christopher J, Weinman, Jerod J, Tran, Lam C, Scharstein, Daniel

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A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction von Kuhn, Andreas, Hirschmüller, Heiko, Scharstein, Daniel, Mayer, Helmut

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Evaluation of Stereo Matching Costs on Images with Radiometric Differences von Hirschmuller, H., Scharstein, D.

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물리적 키보드 추적 von HERLING JAN, SCHARSTEIN DANIEL

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Multi-frame stereo matching with edges, planes, and superpixels von Xue, Tianfan, Owens, Andrew, Scharstein, Daniel, Goesele, Michael, Szeliski, Richard

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View Synthesis Using Stereo Vision von Scharstein, Daniel

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Image-based rendering for scenes with reflections von Sinha, Sudipta N., Kopf, Johannes, Goesele, Michael, Scharstein, Daniel, Szeliski, Richard

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Guest Editorial: Special Issue on Performance Evaluation in Computer Vision von Scharstein, Daniel, Dai, Angela, Kondermann, Daniel, Sattler, Torsten, Schindler, Konrad

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Modeling Radiometric Uncertainty for Vision with Tone-Mapped Color Images von Chakrabarti, Ayan, Xiong, Ying, Sun, Baochen, Darrell, Trevor, Scharstein, Daniel, Zickler, Todd, Saenko, Kate

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High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth von Scharstein, Daniel, Hirschmüller, Heiko, Kitajima, York, Krathwohl, Greg, Nešić, Nera, Wang, Xi, Westling, Porter

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Image-based rendering in the gradient domain von Kopf, Johannes, Langguth, Fabian, Scharstein, Daniel, Szeliski, Richard, Goesele, Michael

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A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors von Szeliski, R., Zabih, R., Scharstein, D., Veksler, O., Kolmogorov, V., Agarwala, A., Tappen, M., Rother, C.

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인공 현실 시스템들에서 평면들을 식별하는 방법 von GERAGHTY DAVID JAMES, SZELISKI RICHARD, SCHARSTEIN DANIEL

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On Learning Conditional Random Fields for Stereo: Exploring Model Structures and Approximate Inference von Pal, Christopher J., Weinman, Jerod J., Tran, Lam C., Scharstein, Daniel

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