Paper Citation Record · LEDGER

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing

As of 16 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:1908.04130.

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pith.paper-citation-record.v1
1908.04130 v2

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Pith citing papers itemized under the disclosed page cap.

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Outbound references

Observation aa9cd843-93dc-41c8-bfc5-11f9469438c2 · outbound

This paper cites A fully automated tortuosity quantiﬁcation system with application to corneal nerve ﬁbres in confocal microscopy images.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing A fully automated tortuosity quantiﬁcation system with application to corneal nerve ﬁbres in confocal microscopy images

Reference 1

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This paper cites Scale and curvature invariant ridge detector for tortuous and fragmented structures.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Scale and curvature invariant ridge detector for tortuous and fragmented structures

Reference 2

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This paper cites DeSTNet: Densely fused spatial transformer networks.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing DeSTNet: Densely fused spatial transformer networks

Reference 3

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Unresolved cited work

Reference 4

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This paper cites Surf: Speeded up robust features.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Surf: Speeded up robust features

Reference 5

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Observation f9f667f6-810c-42a6-b995-e723225d2d86 · outbound

This paper cites Vascular registration in photoacoustic imaging by low- rank alignment via foreground, background and complement decomposition.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Vascular registration in photoacoustic imaging by low- rank alignment via foreground, background and complement decomposition

Reference 6

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Observation 5952550c-dc8f-40a3-9905-fd3c064fb5c4 · outbound

This paper cites Supervised transformer network for efﬁcient face detection.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Supervised transformer network for efﬁcient face detection

Reference 7

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Observation 74d4b8c0-7bf9-489e-8cda-96473bf92496 · outbound

This paper cites Nonconvex plus quadratic penalized low-rank and sparse decomposition for noisy image alignment.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Nonconvex plus quadratic penalized low-rank and sparse decomposition for noisy image alignment

Reference 8

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This paper cites Least squares congealing for unsupervised alignment of images.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Least squares congealing for unsupervised alignment of images

Reference 9

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This paper cites Least-squares congealing for large numbers of im- ages.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Least-squares congealing for large numbers of im- ages

Reference 10

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Observation a46d2cbb-3a2c-4a08-8dd0-9dc49f4b019c · outbound

This paper cites Histograms of oriented gra- dients for human detection.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Histograms of oriented gra- dients for human detection

Reference 11

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This paper cites A modern approach.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing A modern approach

Reference 12

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Fast r-cnn

Reference 13

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This paper cites Multiple view ge- ometry in computer vision.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Multiple view ge- ometry in computer vision

Reference 14

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This paper cites Iterative grassmannian optimization for robust image alignment.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Iterative grassmannian optimization for robust image alignment

Reference 15

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This paper cites Learning to align from scratch.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Learning to align from scratch

Reference 16

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This paper cites Unsu- pervised joint alignment of complex images.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Unsu- pervised joint alignment of complex images

Reference 17

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This paper cites Labeled faces in the wild: A database forstudying face recognition in unconstrained environments.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Labeled faces in the wild: A database forstudying face recognition in unconstrained environments

Reference 18

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Joint registration and synthesis using a probabilistic model for alignment of mri and histo- logical sections

Reference 19

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Kinectfusion: real-time 3d reconstruction and inter- action using a moving depth camera

Reference 20

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This paper cites Warpnet: Weakly supervised matching for single- view reconstruction.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Warpnet: Weakly supervised matching for single- view reconstruction

Reference 21

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This paper cites Labeled faces in the wild: A survey.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Labeled faces in the wild: A survey

Reference 22

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This paper cites Data driven image models through continuous joint alignment.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Data driven image models through continuous joint alignment

Reference 23

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing The mnist database of handwritten digits

Reference 24

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Lagrangian relaxation

Reference 25

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Modiﬁed robust image alignment by sparse and low rank decomposition for highly linearly correlated data

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Inverse compositional spatial transformer networks

Reference 27

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Training invariant support vector machines using selective sampling

Reference 28

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Distinctive image features from scale- invariant keypoints

Reference 29

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing An iterative image reg- istration technique with an application to stereo vision

Reference 30

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Largescale image retrieval with attentive deep local features

Reference 31

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Partial sum minimization of singular values in robust pca: Algorithm and applications

Reference 32

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Efﬁcient mo- tion and disparity estimation optimization for low complex- ity multiview video coding

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Piefa: Personalized incremental and ensemble face align- ment

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Rasl: Robust alignment by sparse and low-rank de- composition for linearly correlated images

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Convo- lutional neural network architecture for geometric matching

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Raps: Robust and efﬁcient automatic construc- tion of person-speciﬁc deformable models

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Robust statistical face frontalization

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Robust statistical frontalization of human and animal faces

Reference 39

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Dis- criminative learning of deep convolutional feature point de- scriptors

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Penalty functions

Reference 41

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Face detection using deep learning: An improved faster rcnn ap- proach

Reference 42

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Unresolved cited work

Reference 43

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Joint data alignment up to (lossy) transformations

Reference 44

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Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Robust real-time face de- tection

Reference 45

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This paper cites A survey on face detection in the wild: past, present and future.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing A survey on face detection in the wild: past, present and future

Reference 46

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This paper cites Learning to com- pare image patches via convolutional neural networks.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Learning to com- pare image patches via convolutional neural networks

Reference 47

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This paper cites Joint face detection and alignment using multitask cascaded convolutional networks.

Jointly Aligning Millions of Images with Deep Penalised Reconstruction Congealing Joint face detection and alignment using multitask cascaded convolutional networks

Reference 48

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