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  1. Results that match 1 of 2 words

  2. Projective Bundle Adjustment from ArbitraryInitialization using the…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2016-ECCV-varpro.pdf
    13 Mar 2018: This initialization is subsequently used as starting point for nonlinearleast-squares optimization (termed bundle adjustment) over all unknowns (see [24] fora review). ... In: Advances in Neural Information Processing Systems 24 (NIPS 2011), pp.406–414
  3. LOGOTHETIS ET AL.: PHOTOMETRIC STEREO IN AMBIENT LIGHT 1 ...

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2016-BMVC-photometric.pdf
    13 Mar 2018: We used 24 LEDs arranged in 2 concentric rings of radii3cm and 5cm respectively. ... Experimental analysis of brdf models. In EGSR,2005. [24] R. Or-el, G.
  4. A Unifying Resolution-Independent Formulation for Early Vision∗ Fabio …

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2012-CVPR-Viola.pdf
    13 Mar 2018: E(U, V) =I F(V)U:ρ+. λ1t. #Tt(V). (ut2ut3)α. p. λ2Rdisc(U, V) (24). ... Port (23.28) LB (24.04) TV (22.26) Our (23.80). Figure 9. Denoising.
  5. Epipolar geometry from profiles under circular motion - Pattern…

    mi.eng.cam.ac.uk/~cipolla/publications/article/2001-PAMI-circular-motion.pdf
    13 Mar 2018: points ux, uy, and uz given by. ux 100. 24 35; uy 010. ... 24 35: 20Therefore, 8; 2 IR, the point. X ÿsin=2; ; cos=2T.
  6. Learning Motion Categories using both Semantic and Structural…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2007-CVPR-Wongsf-learning.pdf
    13 Mar 2018: to sample size)1 5 10 15 20 24. Control set-up 67.46 73.80 77.50 80.37 81.67 83.92Test set-up N/A N/A ... Control set-up involves batch training usingsegmented KTH data (24 samples associated with 1 subject) whiletest set-up involves retraining of an
  7. Incremental Learning of Temporally-CoherentGaussian Mixture Models…

    mi.eng.cam.ac.uk/~cipolla/publications/article/2006-SME-Arandjelovic.pdf
    13 Mar 2018: 18] N. Vlassis and A Likas. A kurtosis-based dynamic approach to Gaussian mixture modeling.Systems, Max, and Cybernetics – Part A: Systems and Humans, 24(9):393–399, 1999.
  8. Learning over Sets using Boosted ManifoldPrincipal Angles (BoMPA)…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2005-BMVC-Kim-BoMPA.pdf
    13 Mar 2018: Afterautomatic localization using a cascaded detector [24] and cropping to the uniform scaleof 5050 pixels, images of faces were histogram equalized, see Figure 6. ... 24] P. Viola and M. Jones. Robust real-time face detection.IJCV, 57(2):137–154, 2004.
  9. The Applications of Uncalibrated Occlusion Junctions A.…

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/1999-BMVC-Broadhurst-applications.pdf
    13 Mar 2018: 7] M.A. FischlerandR.C.Bolles.Randomsampleconsensus:A paradigmfor modelfitting with applicationsto imageanalysisandautomatedcartography. CACM, 24(6):381–395,June1981. [8] R.I.
  10. doi:10.1016/j.imavis.2007.01.006

    mi.eng.cam.ac.uk/~cipolla/archive/Publications/article/2008-IVC-Vogiatzis.pdf
    13 Mar 2018: Fortu-nately a number of efficient approximate algorithms havebeen proposed such as graph cuts [1] and belief propaga-tion [24]. ... 1194–1201. [24] J. Sun, H,-Y Shum, N.-N. Zheng, Stereo matching using beliefpropagation, in: Proceedings of ECCV, 2002,
  11. Deep Roots: Improving CNN Efficiency With Hierarchical Filter Groups

    mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2017-CVPR-deep-roots.pdf
    13 Mar 2018: For training, we used the initialization. scheme described by [24] modified for compound layers [9]. ... To train we used the initialization. of [24] modified for compound layers [9] and batch normal-.

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