Paper Citation Record · LEDGER

Beyond Photo Realism for Domain Adaptation from Synthetic Data

As of 16 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:1909.01960.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1909.01960 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:06:15.637798Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

28 of 28 outbound references displayed

verified exact1
verified fuzzy17
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 46fdc293-f074-4397-b8cf-302ea9eda7a2 · outbound

This paper cites Kernel-predicting convolutional networks for denoising monte carlo ren- derings.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Kernel-predicting convolutional networks for denoising monte carlo ren- derings

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.947302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c60f3648-894e-4f51-9d0f-65068c6139d2 · outbound

This paper cites Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Unsupervised Pixel-Level Domain Adaptation with Generative Adversarial Networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.542652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 864dc15e-d707-4c4c-8b3a-d0aba5d97347 · outbound

This paper cites Alla Chaitanya, Anton S.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Alla Chaitanya, Anton S

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.936827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4a6089b3-d50c-4ef4-b18e-fafb90a8b15c · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Beyond Photo Realism for Domain Adaptation from Synthetic Data ShapeNet: An Information-Rich 3D Model Repository

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.550632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dbf5d1e-1e4e-4829-923e-2461de22392b · outbound

This paper cites Imagenet: A large-scale hierarchi- cal image database.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Imagenet: A large-scale hierarchi- cal image database

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.925284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1f688f24-931d-4877-a39a-31cee5320087 · outbound

This paper cites Ganin and V.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Ganin and V

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.914474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8f2307cb-521c-470b-94f9-cc72da7599e8 · outbound

This paper cites Generative adversarial nets.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Generative adversarial nets

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.902876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 585e5dbc-f971-4ada-a5d4-88ca6cb1ddb4 · outbound

This paper cites Hp 3d scan: Hp ofﬁcial website.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Hp 3d scan: Hp ofﬁcial website

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.892280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 69086045-6684-4ed1-be11-e65a28c931ae · outbound

This paper cites Mitsuba renderer, 2010.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Mitsuba renderer, 2010

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.881641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2593e8aa-9c50-4c33-ad23-cc43e16a5260 · outbound

This paper cites A machine learning approach for ﬁltering monte carlo noise.

Beyond Photo Realism for Domain Adaptation from Synthetic Data A machine learning approach for ﬁltering monte carlo noise

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.871738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8fdf26ca-328b-425c-bde6-874294a842d5 · outbound

This paper cites Learning multiple layers of features from tiny images.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Learning multiple layers of features from tiny images

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.576422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c111442-d213-425e-9ec8-2bdc92af4690 · outbound

This paper cites Lecun, L.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Lecun, L

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.855023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d41ddffb-010a-4b6e-a0bb-ad75d3ee0afc · outbound

This paper cites Learn- ing methods for generic object recognition with invari- ance to pose and lighting.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Learn- ing methods for generic object recognition with invari- ance to pose and lighting

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.844340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 664c76ad-3b60-4795-9850-c6be2b7ce4b4 · outbound

This paper cites Microsoft COCO: Common Objects in Context.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Microsoft COCO: Common Objects in Context

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.587323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94da7f91-dbdf-42f2-b613-ba123b9c9fa3 · outbound

This paper cites Efﬁcient algorithms for local and global accessibility shading.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Efﬁcient algorithms for local and global accessibility shading

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.833624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0af7f409-f689-4573-af68-5ffa0e45587f · outbound

This paper cites Deep Shading: Convolutional Neural Networks for Screen-Space Shading.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Deep Shading: Convolutional Neural Networks for Screen-Space Shading

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.594622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b08a73d-1064-4729-aa1b-405707a2e062 · outbound

This paper cites Physically Based Rendering, Second Edition: From Theory To Imple- mentation.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Physically Based Rendering, Second Edition: From Theory To Imple- mentation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.822528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 032a5ede-ee19-4ef4-9371-696704de04d2 · outbound

This paper cites An efﬁ- cient representation for irradiance environment maps.

Beyond Photo Realism for Domain Adaptation from Synthetic Data An efﬁ- cient representation for irradiance environment maps

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.810452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9e9c4f07-ec96-4bf7-878d-2423bf247665 · outbound

This paper cites Playing for Data: Ground Truth from Computer Games.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Playing for Data: Ground Truth from Computer Games

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.605451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01b3c036-94d9-4975-ba71-7610611a0871 · outbound

This paper cites Compre- hensible rendering of 3-d shapes.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Compre- hensible rendering of 3-d shapes

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.799305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c625f343-38ff-4092-a1f4-ac62f019ff08 · outbound

This paper cites Alla Chaitanya, John Burgess, Shiqiu Liu, Carsten Dachsbacher, Aaron Lefohn, and Marco Salvi.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Alla Chaitanya, John Burgess, Shiqiu Liu, Carsten Dachsbacher, Aaron Lefohn, and Marco Salvi

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.788272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d5735890-2e72-4aa1-9bde-343bd4bad141 · outbound

This paper cites Play and Learn: Using Video Games to Train Computer Vision Models.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Play and Learn: Using Video Games to Train Computer Vision Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.616375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9535d61-3abf-4550-942c-f79bb995054a · outbound

This paper cites Kessenich, and Bill M.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Kessenich, and Bill M

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.776522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 04ac034d-27da-4043-9815-a5c26a91c00a · outbound

This paper cites Learning from Simulated and Unsupervised Images through Adversarial Training.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Learning from Simulated and Unsupervised Images through Adversarial Training

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.623820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b35c82e5-ada5-4852-a878-5cffcd4f0a43 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.627788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f5c9615-f902-4ceb-be5d-4087ba8c5a24 · outbound

This paper cites RenderGAN: Generating Realistic Labeled Data.

Beyond Photo Realism for Domain Adaptation from Synthetic Data RenderGAN: Generating Realistic Labeled Data

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T05:06:15.631183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 084d2e91-c9aa-41a6-bf86-f5eff27fd778 · outbound

This paper cites Bovik, Hamid R.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Bovik, Hamid R

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:06:15.765316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6a92d640-64fa-473b-a5a1-e70c40d69a1c · outbound

This paper cites Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks.

Beyond Photo Realism for Domain Adaptation from Synthetic Data Physically-Based Rendering for Indoor Scene Understanding Using Convolutional Neural Networks

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-14T05:06:15.672699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.