IPDDF: an improved precision dense descriptor based flow estimation
暂无分享,去创建一个
[1] Cordelia Schmid,et al. A Comparison of Affine Region Detectors , 2005, International Journal of Computer Vision.
[2] David G. Lowe,et al. Distinctive Image Features from Scale-Invariant Keypoints , 2004, International Journal of Computer Vision.
[3] Frédo Durand,et al. Bilateral Filtering: Theory and Applications , 2009, Found. Trends Comput. Graph. Vis..
[4] Yasuyuki Matsushita,et al. Motion detail preserving optical flow estimation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[5] Michael J. Black,et al. The Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow Fields , 1996, Comput. Vis. Image Underst..
[6] Pascal Fua,et al. SLIC Superpixels Compared to State-of-the-Art Superpixel Methods , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[7] Antonio Torralba,et al. SIFT Flow: Dense Correspondence across Scenes and Its Applications , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[8] Berthold K. P. Horn,et al. Determining Optical Flow , 1981, Other Conferences.
[9] Jitendra Malik,et al. Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[10] Vibhav Vineet,et al. Filter-Based Mean-Field Inference for Random Fields with Higher-Order Terms and Product Label-Spaces , 2012, International Journal of Computer Vision.
[12] Vincent Lepetit,et al. DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.