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Brostow, G. J.
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1

Learning a Confidence Measure for Optical Flow:

Mac Aodha, Oisin ; Humayun, A. ; Pollefeys, M..
IEEE Transactions on Pattern Analysis and Machine Intelligence.  35 (2013)  5 - p. 1107-1120 , 2013
Link: https://doi.org/10.1109/..
 
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2

Video Normals from Colored Lights:

Brostow, G. J. ; Hernandez, C. ; Vogiatzis, G...
IEEE Transactions on Pattern Analysis and Machine Intelligence.  33 (2011)  10 - p. 2104-2114 , 2011
Link: https://doi.org/10.1109/..
 
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3

Semantic Photo Synthesis:

Johnson, M. ; Brostow, G. J. ; Shotton, J....
Computer Graphics Forum.  25 (2006)  3 - p. 407-413 , 2006
Link: https://doi.org/10.1111/..
 
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4

Two-View Geometry Scoring Without Correspondences:

Barroso-Laguna, A ; Brachmann, E ; Prisacariu, VA..
https://discovery.ucl.ac.uk/id/eprint/10179637/1/Barroso-Laguna_Two-View_Geometry_Scoring_Without_Correspondences_CVPR_2023_paper.pdf.  , 2023
Link: https://discovery.ucl.ac..
 
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5

Heightfields for Efficient Scene Reconstruction for AR:

Watson, J ; Vicente, S ; Aodha, OM...
https://discovery.ucl.ac.uk/id/eprint/10167541/1/Heightfields%20for%20Efficient%20Scene%20Reconstruction%20for%20AR.pdf.  , 2023
Link: https://discovery.ucl.ac..
 
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6

Removing Objects From Neural Radiance Fields:

Weder, S ; Garcia-Hernando, G ; Monszpart, Á...
https://discovery.ucl.ac.uk/id/eprint/10179635/1/Weder_Removing_Objects_From_Neural_Radiance_Fields_CVPR_2023_paper.pdf.  , 2023
Link: https://discovery.ucl.ac..
 
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7

Interactive Sketching of Mannequin Poses:

Unlu, G ; Sayed, M ; Brostow, G
https://discovery.ucl.ac.uk/id/eprint/10167370/1/2212.07098.pdf.  , 2023
Link: https://discovery.ucl.ac..
 
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8

Two-view geometry scoring without correspondences:

Barroso-Laguna, A ; Brachmann, E ; Prisacariu, VA..
doi:10.1109/CVPR52729.2023.00867.  , 2023
Link: https://doi.org/10.1109/..
 
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9

Improved Handling of Motion Blur in Online Object Detection:

Sayed, M ; Brostow, G
https://discovery.ucl.ac.uk/id/eprint/10143471/1/2011.14448.pdf.  , 2021
Link: https://discovery.ucl.ac..
 
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10

Panoptic segmentation forecasting:

Graber, C ; Tsai, G ; Firman, M..
https://discovery.ucl.ac.uk/id/eprint/10165507/1/Graber_Panoptic_Segmentation_Forecasting_CVPR_2021_paper.pdf.  , 2021
Link: https://discovery.ucl.ac..
 
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11

Shazam For Bats: Internet of Things for Continuous Real-Tim..:

Gallacher, S ; Wilson, D ; Fairbrass, A...
https://discovery.ucl.ac.uk/id/eprint/10135165/7/Wilson_Shazam%20For%20Bats-%20Internet%20of%20Things%20for%20Continuous%20Real-Time%20Biodiversity%20Monitoring_VoR.pdf.  , 2021
Link: https://discovery.ucl.ac..
 
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12

Focus on the Positives: Self-Supervised Learning for Biodiv..:

Pantazis, O ; Brostow, G ; Jones, K.
https://discovery.ucl.ac.uk/id/eprint/10133392/1/focus%20on%20the%20positives%20-%20final%20version.pdf.  , 2021
Link: https://discovery.ucl.ac..
 
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13

Self-supervised monocular depth hints:

Watson, J ; Firman, M ; Brostow, G.
https://discovery.ucl.ac.uk/id/eprint/10117262/1/1909.09051.pdf.  , 2020
Link: https://discovery.ucl.ac..
 
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14

Digging into self-supervised monocular depth estimation:

Godard, C ; Aodha, OM ; Firman, M.
https://discovery.ucl.ac.uk/id/eprint/10117263/1/1806.01260.pdf.  , 2019
Link: https://discovery.ucl.ac..
 
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15

CityNet - Deep Learning Tools for Urban Ecoacoustic Assessm..:

Fairbrass, A ; Firman, M ; Williams, C...
https://discovery.ucl.ac.uk/id/eprint/10057890/7/Fairbrass_248708.full.pdf.  , 2018
Link: https://discovery.ucl.ac..
 
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