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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/gee_tr62.pdf9 Aug 2005: 6#M4!$63. <>/N!GM;OP!$Q#R$8270P'SRG2T.B=UV6#XW! G/YX!W$ EZ. []_=aPbc[Ade[AbbgfAhg[AdikjhmlJn)o[)f1lJ[)n=jbI[pjgjef)n]f)e dhAqNn)lJj lGhHnrslJntq. -
Multi-Task Learning Using Uncertainty to Weigh Losses for Scene…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2018-CVPR-multi-task-learning.pdf11 Sep 2019: Firstly, our results show that there is usually not a single op-. -
Filtering Using a Tree-Based Estimator B. Stenger∗ A. Thayananthan∗…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2003-ICCV-Stenger-filtering.pdf13 Mar 2018: Filtering Using a Tree-Based Estimator. B. Stenger A. Thayananthan P. H. S. Torr† R. Cipolla. University of Cambridge † Microsoft Research Ltd.Department of Engineering 7 JJ Thompson AvenueCambridge, CB2 1PZ, UK Cambridge, CB3 OFB, UK. -
Refining Architectures of Deep Convolutional Neural Networks Sukrit…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2016-CVPR-refining-CNN.pdf13 Mar 2018: Please see Fig 1 for an illustration ofthese operations. We do not consider the other plausible op-erations for architectural refinement of CNN; for instance,arbitrary connection patterns between two layers ... 2. We introduce a strategy that starts with -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/blackburn_eurosp95.pdf9 Aug 2005: " #$!&%'! ( )'""$ % #!, -. 0/21'/23547698;:=<>@?BA 1/2CD/EGF9>HAJI. KMLBNPO#QSRUTWVBXZY[#RU]XQ_aRUbacdD[eVfRg[eXhXQSRg[eVjikXlmLnQbSNZX[Wbo@QSpeNqlWRg[mV]bSrf[$s;bhteKMLBNPO#QSRUTWVBX. K'u'vxwhy{z"d|[mVn}ULf[eTXhN0LfRg}M_aO9kX[eV# hL]N L]B p#. q|Z5ZK -
Utilisation de la cohérence globale entre silhouettes pour…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2006-ARIF-Hernandez.pdf13 Mar 2018: intervals de profondeur vides.Dans le cas de deux vues, les silhouettes correspondantesne seront pas cohérentes s’il existe au moins un rayon op-tique classé S par une des silhouettes -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/holden_tr212.pdf9 Aug 2005: "#$ % &! ')( ,-/.#021. 354 6789:6<;>=?8@A6CBD687#E$FGEH9)=JI$7"4 6K@LNM 7POJ8QF8RST8@F@VUWIE$XZYF M E[6<Y>] M 7Z@. _acbPdefhgcikjb:l2a#bjCmnacoqpracbPshtvuwacb"xwacbyz{|D}?sh|s?ceJcc. ma"5 cc. hotpug<utkpa"ativacik#acbgbcg< -
Noname manuscript No.(will be inserted by the editor) Using ...
mi.eng.cam.ac.uk/~cipolla/publications/article/2013-IJCV-dense-AAM.pdf19 May 2014: Dense op-. tical flow is used to compute pairwise registration and. -
Learning Shape Priors for Single View Reconstruction Yu Chen ...
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2009-3DIM-shape-priors.pdf13 Mar 2018: Learning Shape Priors for Single View Reconstruction. Yu Chen and Roberto CipollaDepartment of Engineering, University of Cambridge. {yc301 and rc10001}@cam.ac.uk. Abstract. In this paper, we aim to reconstruct free-from 3D mod-els from a single -
Multi-View Depth Estimation by FusingSingle-View Depth Probability…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2022-CVPR-multiview-depth-fusion.pdf13 Mar 2023: Note that the consistencyweighting alone can improve the accuracy (for Ns 19).This suggests that the proposed weighting can be applied tothe existing multi-view depth estimation methods that op-erate -
Statistical Models forNoise-Robust Speech Recognition R O G I ...
mi.eng.cam.ac.uk/~mjfg/thesis_rcv25.pdf7 Oct 2011: Statistical Models forNoise-Robust. Speech Recognition. R O G I E R C H R I S T I A A NV A N D A L E N. Q U E E N S ’ C O L L E G E. Department of EngineeringUniversity of Cambridge. is dissertation is submitted for the degree of Doctor of -
Augmented Statistical Models for Classifying Sequence Data Martin…
mi.eng.cam.ac.uk/~mjfg/thesis_ml362.pdf16 Jan 2008: Augmented Statistical Models for. Classifying Sequence Data. Martin Layton. Corpus Christi College. University of Cambridge. September 2006. Dissertation submitted to the University of Cambridge. for the degree of Doctor of Philosophy. i. -
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mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/1994-ECCV-Lawn-egomotion.pdf13 Mar 2018: tDvxmKyz{ag/koamn|@p s p}l}op z{ygKa. mm m. dKm pjym gp}@z{pg s kl z{ygKa. ... 4"<4L86"< )&A$"%( OP SOH! "% $ &%& 6 2 /, 1 ,"%5="% w4"< 2 "< 9 4w" 2 wZJ> 4w"%H7L. -
Hole Filling Through Photomontage Marta Wilczkowiak∗, Gabriel J.…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2005-BMVC-Wilczkowiak-hole-filling.pdf13 Mar 2018: Now the problem of finding an op-timal replacement of pixels in patch p′ from those in patch m′ is equivalent to finding apath in the graph such that the error -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/rohling_tr270.pdf9 Aug 2005: p'q'P O[q2OtP2QpGTYq2stQp'Qrj¡Op'q.Qq'u)xIQGPkq'QU£q2stQ,P2QGN)M?p2q'P kq2MIu)w«k/xIN/u/P -
SegNet: A Deep Convolutional Encoder-Decoder Architecture for…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2015-arxiv-SegNet.pdf13 Mar 2018: LeCun. Sceneparsing with multiscale feature learning, purity trees, and op-timal covers. -
Noname manuscript No.(will be inserted by the editor) Using ...
mi.eng.cam.ac.uk/~cipolla/archive/Publications/article/2014-IJCV-dense-AAM.pdf13 Mar 2018: Dense op-. tical flow is used to compute pairwise registration and. -
Uncertainty Decoding forNoise Robust Speech Recognition Hank Liao…
mi.eng.cam.ac.uk/~mjfg/thesis_hl251.pdf17 Sep 2008: 8.10 WER (%) and log-likelihood for VTS compensation of clean models on Op-erations Room corrupted RM task at 20 dB SNR (0DA) varying dimensionscompensated and noise model estimation. -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/rummery_tr166.pdf9 Aug 2005: "#%$" &'. (!),).-0/1!12436587:9;)=<?>@3ACB DACB EF=GH G? IF=JLK=MNM. OP24QPR241,S243JT4UCUWV. X0AC1,S36>ZY+[C2,IBP>Z]C243_>ZR5aBP[b>cBP2 243_>cBP[de24QAb36Rf1,24BbRg 3h/1!QP>@BP[CRijBOPRf362 2 RX0AC1,S36>ZY+[C2X0kHlT mn. aBP[Co@ACBPY. -
bmvc-99.dvi
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/1999-BMVC-Chesi.pdf13 Mar 2018: 2Gênu£¢£nZ»i{ki£ªn¢a£ªs£iiÓ]i]n¢«sx¢g¤K1 ¡¥£B¢ai«Åig¢]s£iªs¢£g Ói isÅ1{Z£i3ìs«¥Â£pi£¥NM%¤n]kg]iPO ¢ ¡¥s£<-¿! $. iÓ]i]n¢n¥«¥ÅspJKs P I6¥««3¤Kªs£g Óª££g MV OP I V -
report.dvi
mi.eng.cam.ac.uk/reports/svr-ftp/liao_tr499.pdf26 Sep 2005: CAMBRIDGE UNIVERSITYENGINEERING DEPARTMENT. Uncertainty Decoding for. Noise Robust. Automatic Speech Recognition. H. Liao and M.J.F. Gales. CUED/F-INFENG/TR.499. October 2004 (Revised January 2005). Cambridge University Engineering Department. -
Noname manuscript No.(will be inserted by the editor) Using ...
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2013-Anderson-IJCV.pdf19 May 2014: Dense op-. tical flow is used to compute pairwise registration and. -
A Simple Technique for Self-Calibration
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/1999-CVPR-Mendonca-self-calibration.pdf13 Mar 2018: This goal is achieved by solving an op-timization problem by numerical techniques, searching di-rectly for the intrinsic parameters of the cameras, instead ofthe indirect search performed by the algorithms -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/gee_tr100.pdf9 Aug 2005: A:gX BYh[8143U5 7/9;:A<. i. v. (1)gradient of objective. using. = v (. v. v++ iop. )op. v. t T. sT= valv. 1. 0 1. -
Fast surface and volume estimationfrom non-parallel cross-sections,…
mi.eng.cam.ac.uk/reports/svr-ftp/treece_tr326.pdf20 Dec 1999: 3 o. r 6. Deg. rees. of. Fre. edo. m). Op. -
icra00.dvi
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2000-ICRA-Chesi.pdf13 Mar 2018: ÑÕOLÔ Ô ÓP BQRL(STUWÒzØ BVÒzØeÔ6Ñ! , -
Multi-Sensory Face Biometric Fusion (for Personal Identification)…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2006-OTCBVS-Arandjelovic-fusion.pdf13 Mar 2018: The optimal. values were found to be2.3 and6.2 for visual data; the op-timal filter for thermal data was found to be alow-passfilterwith W2 = 2.8 (i.e. -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/ahadi_thesis.pdf9 Aug 2005: a. )]H OP<P" /? 45 0: , 7< > 7 &. ))6!$ )G@ F), /-$ /) ,,. 3 B3% OP<P" /? 45 :3 , I 42$ % ; C / M:E- ) / <L# :5; 3 C% - P: F) / )C ,). -
Silhouette-based Object Phenotype Recognition using 3D Shape Priors…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2011-ICCV-Chen-priors.pdf13 Mar 2018: However, the back-projectionfrom 2D to 3D is usually multi-modal, and this results ina non-convex objective function with multiple local op-tima, which is usually difficult to solve. -
Kernel Methods forText-Independent Speaker Verification Chris…
mi.eng.cam.ac.uk/~mjfg/thesis_cl336.pdf25 Feb 2010: Kernel Methods forText-Independent. Speaker Verification. Chris Longworth. Cambridge University Engineering Departmentand. Christ’s CollegeFebruary 23, 2010. Dissertation submitted to the University of Cambridgefor the degree of Doctor of -
Contour-Based Learning for Object Detection Jamie ShottonDepartment…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2005-ICCV-Shotton-object-detection.pdf13 Mar 2018: Horses were investigatedbriefly in [7] but poor results were obtained. 3Note that ROC curves are not ideal for the task of detection, as op-posed to classification; see [1] for more -
Ghostscript wrapper for…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2007-CVPR-Kim-tensor.pdf13 Mar 2018: rize human action and gesture classes in videos. Traditional. approaches based on explicit motion estimation require op-. -
Parcel:feature subset selectionin variable cost domains M.J.J. Scott, …
mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/Scott_tr323.pdf9 Aug 2005: Englandemail: mjjs@eng.cam.ac.uk. ii. iii. Abstract. The vast majority of classification systems are designed with a single set of features, and op-timised to a single specified cost. -
DEEP-CARVING: Discovering Visual Attributes by Carving Deep Neural…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2015-CVPR-Shankar.pdf13 Mar 2018: ntr. op. y L. os. s. Inp. ut. Ima. ge. L1. -
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mi.eng.cam.ac.uk/~cipolla/publications/article/1998-IJCV-quasi-invariants.pdf13 Mar 2018: 1 1R@ ' 01. ë5ãèéèê79 C1 = @ øAèàòáèå áãè øAèáèéõäÎàçàÒá ò ö çõVçáéä)ùTë5ãAäñã ñò àåäåáådò ö áë5òñò)ï:õà ìÒèñáòéåê 1 = & (-ãè éäÎíãAáãçàødåQäJø:è ò öP' -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/dance_tr273.pdf9 Aug 2005: pyEkEy2U ;=;H7bDlxt{;<y k3yEpuc kEtxpd9m)7%| tumotxyE;<>k'U ; wpucmo;op-q k'U ;)Dl;<:<pd9 y kDEc :<kEtxpd9 q pdD(:<pd9bw;|L:<pd9bkEpdcD(yE;<Fdmo;H9bkEy7b9 >gmotu9 tumotxyE;<> ... 9 y kE;H7->op-q&;H9bq#pdDl:<tu9 F :<pGU ;HDl;H9 :<;Q]d73m pdDl;yEpdj;U -
Linear Gaussian Models for Speech Recognition Antti-Veikko Ilmari…
mi.eng.cam.ac.uk/~mjfg/thesis_avir2.pdf16 Nov 2007: Linear Gaussian Models for. Speech Recognition. Antti-Veikko Ilmari Rosti. Wolfson College. May 2004. Dissertation submitted to the University of Cambridge. for the degree of Doctor of Philosophy. ii. Declaration. This dissertation is the result of -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/holden_tr155.pdf9 Aug 2005: " $#%&%'( )! -,.'/1024365798:,"/;.'/48=<>.@?A,B.'/1CED F.'/'G.'/HEIKJMLON'PQR(CPSJTCVUON'W6XV2ZY[[]Y@_. ab5-cd,"FOYeAfgY@_. Wg5h.'iAid,.'FjD /. -
Model-based Approaches to Robust SpeechRecognition in Diverse…
mi.eng.cam.ac.uk/~mjfg/thesis_yw293.pdf27 Oct 2015: Model-based Approaches to Robust SpeechRecognition in Diverse Environments. Yongqiang Wang. Darwin CollegeEngineering Department Cambridge University. October 2015. This dissertation is submitted to the University of Cambridge. for the degree of -
The State Based Mixture of Experts HMM with Applications ...
mi.eng.cam.ac.uk/reports/svr-ftp/tuerk_thesis.pdf2 Feb 2002: The State Based Mixture of Experts HMM. with Applications to the. Recognition of Spontaneous Speech. Andreas Tuerk. Emmanuel College. and. Cambridge University Engineering Department. September 2001. Dissertation submitted to the University of -
A Differential Volumetric Approach to Multi-View Photometric Stereo…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2019-ICCV-Differential-MVPS.pdf12 Aug 2019: Recently, Park etal. [35] proposed a refinement method by computing an op-tical displacement map in the same 2D planar domain of thephotometric stereo images. -
ZHANG ET AL.: IMAGE RERANKING USING PRETRAINED VISION TRANSFORMERS ...
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2022-BMVC-Zhang-Image-Retrieval.pdf13 Mar 2023: 3. We apply the attention-based relevancy maps tied to vision transformers to guide op-timal transport optimization and further validate the effectiveness of partial optimaltransport for dataset showing strong viewpoint -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/sato_cipollaIJCV98.pdf9 Aug 2005: 1 1R@ ' 01. ë5ãèéèê79 C1 = @ øAèàòáèå áãè øAèáèéõäÎàçàÒá ò ö çõVçáéä)ùTë5ãAäñã ñò àåäåáådò ö áë5òñò)ï:õà ìÒèñáòéåê 1 = & (-ãè éäÎíãAáãçàødåQäJø:è ò öP' -
Hierarchical Kinematic Probability Distributions for 3D Human Shape…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-ICCV-3D-human-shape-in-wild.pdf9 Apr 2022: To allow forthe backpropagation of gradients through the sampling op-eration, we present a differentiable rejection sampler formatrix-Fisher distributions over relative 3D joint rotations. -
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mi.eng.cam.ac.uk/reports/svr-ftp/auto-pdf/drummond_ijcv99.pdf9 Aug 2005: "!$##&%' (" '), -(." /0 213"45" 67"895;:77 89<'="'<>?3< @A B.C 27DE 5@ A"6&8 F3=GH@ ="'9 767<>B. IKJLJNMPO2QR&S0O$TVUWTVXZY[O$]IM$_VaLbGRdceS0TgfhO$cHijRkMmlnab0opTqO$UL_. rts&uhv&wxtuyuzs&{-v}|t{-vwas&;w0rts}"s&|V 2- 27V72 j" ¡ ¢$£. -
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mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2000-ECCV-Drummond.pdf13 Mar 2018: cayxC]VYVz]jrZ%_;sGhmtGg%VjGk,{|j[r}5. CR07#%Y'bR%. Y Y¡.¢¤£% ¥ -
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calib.dvi
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2000-ECCV-Malis.pdf13 Mar 2018: " #$% #&')(,%-&-./0 #1%2%-&-3145 6789. ,9:0;) ". <>=-?A@CB,D4EA?GFHDJIKML@JNPO-QSRS@7TH?AU2@VEAEAD. WXZY%[XV] ]_[XZYa]_bdc-feg+]_X4ehVic-g&jJ[lkJY%]mHXZ[no]_pf[qesrt2uVgbZ[XZY-ev%Xxwyef] ]_ehZiz{'| }0ic-g&jJ[lkJY%]. -ZyP%Joo%y-o-yf%_yPoyo -
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