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Towards Learning Orientated Assessment for Non-native Learner Spoken…
mi.eng.cam.ac.uk/~mjfg/ALTA/presentations/ALTA_Sheffield_20190306.pdf21 Feb 2022: 300 300. 25.5. 400 24.5. 400 24.4. ASR on Non-native Speech (2). • ... Thai dh d 7.24 oh aa 5.21. 30. • Top 2 recurrent substitution errors for speakers in each L1. -
Paper8-CV-intro.dvi
mi.eng.cam.ac.uk/~cipolla/lectures/PartIB/old/2022-IB-Paper8-CV-Introduction.pdf26 Apr 2022: 2D array I(x,y,t) incomputer memory. CCD. • A typical digital SLR CCD measures about 24 16 mm. -
Applying Deep Learning in Non-native Spoken English Assessment
mi.eng.cam.ac.uk/~mjfg/ALTA/presentations/APSIPA2019_Knill.pdf21 Feb 2022: 1.0 indicates within one CEFR grade-level. 24/45. Assessment System Performance. • ... 1.0 indicates within one CEFR grade-level. 24/45. Performance Analysis. 25/45. -
Home Research News Low-cost AI heart monitor developed by ...
mi.eng.cam.ac.uk/~cipolla/archive/Public-Understanding/2018-ECG-Cambridge-Heartwear.pdf9 Apr 2022: This requires fixing 12 leads tothe patient’s chest and carrying the cumbersome device around for 24 hours. -
Use of Deep Learning in Free Speaking Non-native English Assessment
mi.eng.cam.ac.uk/~mjfg/ALTA/presentations/TSD2021_Knill.pdf21 Feb 2022: 24/56. Deep Density Network-based Grader [1, 7]. • Deep Density Networks predict parameters of a distribution. -
Part IA Computing CourseLent Term Software Design Exercise Roberto ...
mi.eng.cam.ac.uk/~cipolla/resource/lent.pdf12 Apr 2022: default:cout << "Trading error: trading system failure." << endl;exit(-1);. }}. 24. -
FIERY: Future Instance Prediction in Bird’s-Eye Viewfrom Surround…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-ICCV-Future-Instance-Prediction-BEV.pdf9 Apr 2022: 5.3. Analysis. 20 22 24 26 28 30. FIERY. Deterministic. Uniform depth. ... 24] Alex Kendall, Yarin Gal, and Roberto Cipolla. Multi-tasklearning using uncertainty to weigh losses for scene geome-. -
Real-time analogue gauge transcription on mobile phone Ben…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-CVPR-analogue-meter-reading.pdf9 Apr 2022: 13]Gauge µθ R% µθ R%meter a 9.24 100 36.51 100meter b 26.06 100 103.63 100meter c 1.94 100 127.68 32.5meter d ... 2. [24] Apostolia Tsirikoglou, Joel Kronander, Magnus Wrenninge,and Jonas Unger. Procedural modeling and physically basedrendering for -
Estimating and Exploiting the Aleatoric Uncertaintyin Surface Normal…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-ICCV-surface-normal-uncertainty.pdf9 Apr 2022: 4Ours S 16.0 8.4 24.7 59.0 77.5 83.7. ... 24] Shuai Liao, Efstratios Gavves, and Cees GM Snoek. Spheri-cal regression: Learning viewpoints, surface normals and 3drotations on n-spheres. -
FIERY: Future Instance Prediction in Bird’s-Eye Viewfrom Surround…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-FIERY-future-instance-BEV.pdf9 Apr 2022: 20 22 24 26 28 30. FIERY. Deterministic. Uniform depth. No future flow. ... 24.6. 24.1. Figure 5: Performance comparison of various ablations ofour model. -
SENGUPTA ET AL.: PROBABILISTIC HUMAN SHAPE & POSE WITH ...
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-BMVC-body-measurement-reconstruction.pdf9 Apr 2022: multiple images of a subject.SMPL [24] is a parametric 3D human body model. ... 24] Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J.Black. -
X-MAN: Explaining multiple sources of anomalies in video Stanislaw ...
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-CVPR-XMAN-anomaly-detection.pdf9 Apr 2022: An alternative approach is using or learningthese feature representations with out of distribution detec-tion algorithms [4, 22, 6], as can be done for anomaly detec-tion [18, 24, 27] or ... Garnett, editors, NIPS, pages 91–99. Curran Associates,Inc., -
ENGINEERING TRIPOS PART IIB ELECTRICAL AND INFORMATION SCIENCES…
mi.eng.cam.ac.uk/~cipolla/resource/4F12exam.pdf12 Apr 2022: with (X, Y ) vertices (23, 3), (5, 30), (45, 24) and (15, 48), calcu-late bounds on s. -
Real-time analogue gauge transcription on mobile phone Ben…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-CVPR-analogue-meter-reading.pdf9 Apr 2022: 13]Gauge µθ R% µθ R%meter a 9.24 100 36.51 100meter b 26.06 100 103.63 100meter c 1.94 100 127.68 32.5meter d ... 2. [24] Apostolia Tsirikoglou, Joel Kronander, Magnus Wrenninge,and Jonas Unger. Procedural modeling and physically basedrendering for -
Estimating and Exploiting the Aleatoric Uncertaintyin Surface Normal…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-ICCV-surface-normal-uncertainty.pdf9 Apr 2022: 4Ours S 16.0 8.4 24.7 59.0 77.5 83.7. ... 24] Shuai Liao, Efstratios Gavves, and Cees GM Snoek. Spheri-cal regression: Learning viewpoints, surface normals and 3drotations on n-spheres. -
SENGUPTA ET AL.: PROBABILISTIC HUMAN SHAPE & POSE WITH ...
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-BMVC-body-measurement-reconstruction.pdf9 Apr 2022: multiple images of a subject.SMPL [24] is a parametric 3D human body model. ... 24] Matthew Loper, Naureen Mahmood, Javier Romero, Gerard Pons-Moll, and Michael J.Black. -
Scaling digital screen reading with one-shot learning and…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-WACV-scaling-digital-meters.pdf9 Apr 2022: Other works have ex-plored using adversarial training to learn how to transfer toa common feature space [24, 16] or adapt synthetic imagesso they look as real as possible [23, 19]. ... In CVPR, 2017. [24] Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor -
R. MECCA ET. AL : LUCES: NEAR-FIELD PHOTOMETRIC STEREO ...
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-BMVC-LUCES-photometric-stereo-dataset.pdf9 Apr 2022: Cup Owl. Queen Squirrel. Bowl Tool. L17-[19] Q18-[27] S20-[32] L20-[17]. 0 6 12 18 24 30. ... SIAM Journal on Imaging Sciences, 7(2):579–612, 2014. doi: 10.1137/120902458. [24] R. -
Lifted Semantic Graph Embedding for Omnidirectional Place Recognition
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-3DV-omnidirectional-localisation.pdf9 Apr 2022: We adapt the graph embeddingnetwork from [24] to learn the graph similarity for imageretrieval. ... 24/7 place recognition by viewsynthesis. In CVPR, pages 1808–1817, 2015. 4321. -
solutions2.dvi
mi.eng.cam.ac.uk/~cipolla/lectures/4F12/Examples/solutions/4F12-examples-2-solutions.pdf17 Oct 2022: The four points can be permuted 4! = 24 different ways. -
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: 2b A. 3 M = exp(b42. )(4b. )24 repeat5 Sample ϵ N(04, I4)6 y = (1). ... 24] Diederik P Kingma and Max Welling. Auto-encoding varia-tional bayes, 2014. -
X-MAN: Explaining multiple sources of anomalies in video Stanislaw ...
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-CVPR-XMAN-anomaly-detection.pdf9 Apr 2022: An alternative approach is using or learningthese feature representations with out of distribution detec-tion algorithms [4, 22, 6], as can be done for anomaly detec-tion [18, 24, 27] or ... Garnett, editors, NIPS, pages 91–99. Curran Associates,Inc., -
Probabilistic 3D Human Shape and Pose Estimation From Multiple…
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-CVPR-3D-body-shape-in-wild.pdf9 Apr 2022: volume 24, pages 408–416, 2005. [3] Anurag Arnab, Carl Doersch, and Andrew Zisserman. ... Conference on Learning Representations (ICLR), 2015. [24] Diederik P. Kingma and Max Welling. -
Part IA Computing CourseTutorial Guide to C++ Programming Roberto ...
mi.eng.cam.ac.uk/~cipolla/resource/tutorial.pdf12 Apr 2022: 24. // testing for real solutions to a quadraticd = bb - 4ac;if(d >= 0.0){. // -
Scaling digital screen reading with one-shot learning and…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-WACV-scaling-digital-meters.pdf9 Apr 2022: Other works have ex-plored using adversarial training to learn how to transfer toa common feature space [24, 16] or adapt synthetic imagesso they look as real as possible [23, 19]. ... In CVPR, 2017. [24] Eric Tzeng, Judy Hoffman, Kate Saenko, and Trevor -
R. MECCA ET. AL : LUCES: NEAR-FIELD PHOTOMETRIC STEREO ...
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-BMVC-LUCES-photometric-stereo-dataset.pdf9 Apr 2022: Cup Owl. Queen Squirrel. Bowl Tool. L17-[19] Q18-[27] S20-[32] L20-[17]. 0 6 12 18 24 30. ... SIAM Journal on Imaging Sciences, 7(2):579–612, 2014. doi: 10.1137/120902458. [24] R. -
Paper8-features-matching.dvi
mi.eng.cam.ac.uk/~cipolla/lectures/PartIB/old/2022-IB-Paper8-CV-Features-Matrching.pdf26 Apr 2022: outliers in the output of the corner detector. 24 Engineering Part IB: Paper 8 Feature extraction and matching. -
Lifted Semantic Graph Embedding for Omnidirectional Place Recognition
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-3DV-omnidirectional-localisation.pdf9 Apr 2022: We adapt the graph embeddingnetwork from [24] to learn the graph similarity for imageretrieval. ... 24/7 place recognition by viewsynthesis. In CVPR, pages 1808–1817, 2015. 4321. -
Hierarchical Kinematic Probability Distributions for 3D Human Shape…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-ICCV-3D-human-shape-in-wild.pdf9 Apr 2022: 2b A. 3 M = exp(b42. )(4b. )24 repeat5 Sample ϵ N(04, I4)6 y = (1). ... 24] Diederik P Kingma and Max Welling. Auto-encoding varia-tional bayes, 2014. -
Probabilistic 3D Human Shape and Pose Estimation From Multiple…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-CVPR-3D-body-shape-in-wild.pdf9 Apr 2022: volume 24, pages 408–416, 2005. [3] Anurag Arnab, Carl Doersch, and Andrew Zisserman. ... Conference on Learning Representations (ICLR), 2015. [24] Diederik P. Kingma and Max Welling. -
PX-NET: Simple and Efficient Pixel-Wise Trainingof Photometric Stereo …
mi.eng.cam.ac.uk/~cipolla/publications/inproceedings/2021-ICCV-PX-NET-photometric-normals.pdf9 Apr 2022: These include lightsource brightness calibration [24] uncertainty and near lightattenuation (as in reality point light sources are not infinitelyfar away) which affect pixel brightness in a multiplicativeway. ... 2. [24] Fotios Logothetis, Roberto Mecca, -
ACCEPTED FOR PUBLICATION IN IEEE/ACM TRANSACTIONS ON AUDIO, SPEECH,…
mi.eng.cam.ac.uk/~mjfg/ALTA/publications/IEEEACMTransASLP2022_Ragni_Confidence.pdf11 Apr 2022: The notion of stability gave rise toalternative language model assessment criteria [23], data aug-mentation methodologies [24] as well as confidence estimationapproaches [16]. ... The speech recogniserwas used to produce a set of lattices using a default -
Improving Attention-based Sequence-to-sequence Models
mi.eng.cam.ac.uk/~mjfg/thesis_qd212.pdf5 Jul 2022: previoustokens. To achieve more accurate estimation, sequence-to-sequence models are usuallyautoregressive [24]. For autoregressive models, a standard approach is teacher forcing, which guides a modelwith reference output history during training. -
PX-NET: Simple and Efficient Pixel-Wise Trainingof Photometric Stereo …
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-ICCV-PX-NET-photometric-normals.pdf9 Apr 2022: These include lightsource brightness calibration [24] uncertainty and near lightattenuation (as in reality point light sources are not infinitelyfar away) which affect pixel brightness in a multiplicativeway. ... 2. [24] Fotios Logothetis, Roberto Mecca, -
Vision Encoders in Visual Question Answering
mi.eng.cam.ac.uk/~wjb31/Ryan_Anderson_Vision_Encoders_in_VQA.pdf10 Sep 2022: 23. 4.3.1 Prompt format. 23. 4.3.2 Building the prompt embedding. 24. -
FIERY: Future Instance Prediction in Bird’s-Eye Viewfrom Surround…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-ICCV-Future-Instance-Prediction-BEV.pdf9 Apr 2022: 5.3. Analysis. 20 22 24 26 28 30. FIERY. Deterministic. Uniform depth. ... 24] Alex Kendall, Yarin Gal, and Roberto Cipolla. Multi-tasklearning using uncertainty to weigh losses for scene geome-. -
FIERY: Future Instance Prediction in Bird’s-Eye Viewfrom Surround…
mi.eng.cam.ac.uk/~cipolla/archive/Publications/inproceedings/2021-FIERY-future-instance-BEV.pdf9 Apr 2022: 20 22 24 26 28 30. FIERY. Deterministic. Uniform depth. No future flow. ... 24.6. 24.1. Figure 5: Performance comparison of various ablations ofour model.
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