Paper Citation Record · LEDGER

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting

As of 22 August 2026, this Paper Citation Record lists 79 of 79 outbound references and 2 inbound Pith citation observations for arXiv:2412.00177.

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

pith.paper-citation-record.v1
2412.00177 v3

Coverage vector

measured 79 of 79 reference resolution

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measured 81 of 81 standing notices

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measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:35:50.655346Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T05:07:38.801117Z

Reference resolution

79 of 79 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c42d569-e862-4757-b613-261ae5710565 · outbound

This paper cites Shape, illumination, and reflectance from shading.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Shape, illumination, and reflectance from shading

Reference 1

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Observation 76fed62c-3680-4b81-af95-a53c2b68290c · outbound

This paper cites Barrow and J.M.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Barrow and J.M

Reference 2

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Observation 91b015e5-4d90-4abc-bea6-45c1296c89a5 · outbound

This paper cites Shadingnet: Image intrinsics by fine-grained shading decomposition.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Shadingnet: Image intrinsics by fine-grained shading decomposition

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:08.031673Z

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Observation defae5f6-0672-4e36-8337-f9290625c1a7 · outbound

This paper cites Cut-and-paste object insertion by enabling deep image prior for reshading.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Cut-and-paste object insertion by enabling deep image prior for reshading

Reference 4

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Observation 1d10b060-6b61-4bbf-a305-88a3305250aa · outbound

This paper cites Stylegan knows normal, depth, albedo, and more.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Stylegan knows normal, depth, albedo, and more

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:08.002149Z

Source-reported events for the cited work

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Observation 797d7b51-e726-4ec7-8aa5-8114b62e7992 · outbound

This paper cites Make It So: Steering StyleGAN for Any Image Inversion and Editing.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Make It So: Steering StyleGAN for Any Image Inversion and Editing

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:46:06.999216Z

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Observation a0c803b3-0a20-4d83-bd9d-0f2f9d72db01 · outbound

This paper cites an unresolved cited work.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Unresolved cited work

Reference 7

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Observation bf31477f-89a5-499e-9d5a-dbf56a75614b · outbound

This paper cites Real-time 3d-aware portrait video relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Real-time 3d-aware portrait video relighting

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.972705Z

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Observation 176f8c96-746f-4c9c-96e8-d730d204b55b · outbound

This paper cites Intrinsic image decomposi- tion via ordinal shading.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Intrinsic image decomposi- tion via ordinal shading

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.958437Z

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Observation d21c6a7a-e466-4762-83f0-fbb6a3b6aade · outbound

This paper cites Colorful diffuse intrinsic image decomposition in the wild.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Colorful diffuse intrinsic image decomposition in the wild

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.943225Z

Source-reported events for the cited work

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Observation 80e77471-ea16-48b0-be27-a849073162a8 · outbound

This paper cites Intrinsic harmonization for illumination-aware image com- positing.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Intrinsic harmonization for illumination-aware image com- positing

Reference 11

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Observation da4ea591-4880-45da-899a-deb15b287f25 · outbound

This paper cites Scribblelight: Single image indoor relighting with scribbles.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Scribblelight: Single image indoor relighting with scribbles

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.912703Z

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Observation 8f41f4ac-4f13-405f-a883-3d50d3a412d4 · outbound

This paper cites Pie-net: Pho- tometric invariant edge guided network for intrinsic image decomposition.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Pie-net: Pho- tometric invariant edge guided network for intrinsic image decomposition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.897531Z

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Observation c6ab3115-9669-47fa-92a2-f19f3bcff47f · outbound

This paper cites Flashtex: Fast relightable mesh texturing with lightcontrolnet.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Flashtex: Fast relightable mesh texturing with lightcontrolnet

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.882527Z

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Observation 0ea91a98-c0c4-4b49-aed6-7413c9fb1c62 · outbound

This paper cites Intrinsic single-image hdr reconstruction.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Intrinsic single-image hdr reconstruction

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.866139Z

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Observation 7de27e69-3248-411a-8466-0bb67449ca09 · outbound

This paper cites Generative Models: What Do They Know? Do They Know Things? Let's Find Out!.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Generative Models: What Do They Know? Do They Know Things? Let's Find Out!

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.460632Z

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Observation 471bcb8d-81fb-406f-96e8-b76bac90f103 · outbound

This paper cites Multi-view intrinsic im- ages of outdoors scenes with an application to relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Multi-view intrinsic im- ages of outdoors scenes with an application to relighting

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.849158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 07c3651d-0036-4444-9325-f53924cddf72 · outbound

This paper cites Intrinsic image decom- position using paradigms.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Intrinsic image decom- position using paradigms

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.833214Z

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Observation 809503e9-d31f-4914-b04c-d0156e9c220f · outbound

This paper cites Spotlight: Shadow-guided object relighting via dif- fusion.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Spotlight: Shadow-guided object relighting via dif- fusion

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.474563Z

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Observation 6380d729-59bf-4708-b673-238861bc556f · outbound

This paper cites Relightable 3D Gaussians: Realistic Point Cloud Relighting with BRDF Decomposition and Ray Tracing.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Relightable 3D Gaussians: Realistic Point Cloud Relighting with BRDF Decomposition and Ray Tracing

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.479396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a749bf80-5360-45d6-bbd4-7a9adf87c42f · outbound

This paper cites A survey on intrinsic images: Delv- ing deep into lambert and beyond.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting A survey on intrinsic images: Delv- ing deep into lambert and beyond

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.818306Z

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Observation 38bd8d71-9c71-4b80-befb-aad4941c348c · outbound

This paper cites The sky’s the limit: Relightable outdoor scenes via a sky-pixel constrained illumination prior and outside-in visibility.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting The sky’s the limit: Relightable outdoor scenes via a sky-pixel constrained illumination prior and outside-in visibility

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.802594Z

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Observation 0966733e-c444-4e8e-93f0-ac93d2ac16f4 · outbound

This paper cites Towards a perceptual evaluation framework for lighting estimation.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Towards a perceptual evaluation framework for lighting estimation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.786490Z

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Observation 5947fd79-b1ea-44b5-afea-e46abcfe56c6 · outbound

This paper cites Denoising diffu- sion probabilistic models.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Denoising diffu- sion probabilistic models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.497646Z

Source-reported events for the cited work

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Observation a9dbf798-f6f4-43d2-a582-37bbb53372f0 · outbound

This paper cites Sa- ae for any-to-any relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Sa- ae for any-to-any relighting

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.760002Z

Source-reported events for the cited work

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Observation 020f01ae-7c03-4a73-94df-b7d0e6f93577 · outbound

This paper cites Nerf- facelighting: Implicit and disentangled face lighting rep- resentation leveraging generative prior in neural radiance fields.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Nerf- facelighting: Implicit and disentangled face lighting rep- resentation leveraging generative prior in neural radiance fields

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.744433Z

Source-reported events for the cited work

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Observation 2c1ea628-0548-49c2-a4d9-98c715e7983d · outbound

This paper cites Neu- ral gaffer: Relighting any object via diffusion.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Neu- ral gaffer: Relighting any object via diffusion

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.510458Z

Source-reported events for the cited work

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Observation 34f52072-b7e7-4258-a6f6-97cd15231a58 · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting A style-based generator architecture for generative adversarial networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.718778Z

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Observation 05262f97-09f6-41c5-8f85-27c0a0e4efbb · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting 3d gaussian splatting for real-time radiance field rendering

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.704353Z

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Observation 0f9202d3-3033-45f4-b171-ff2471a8ded9 · outbound

This paper cites Switchlight: Co-design of physics- driven architecture and pre-training framework for human portrait relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Switchlight: Co-design of physics- driven architecture and pre-training framework for human portrait relighting

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.689313Z

Source-reported events for the cited work

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Observation d095d6d3-8d89-45ef-b702-54314793664c · outbound

This paper cites LightIt: Illumination Modeling and Control for Diffusion Models.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting LightIt: Illumination Modeling and Control for Diffusion Models

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:46:06.856550Z

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Observation cbe0eedd-7f69-4400-b7f8-2bf95a19af46 · outbound

This paper cites In- trinsic image diffusion for single-view material estimation.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting In- trinsic image diffusion for single-view material estimation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.673104Z

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Observation 29366a86-6903-4013-baa8-313e4c9e6457 · outbound

This paper cites The retinex theory of color vision.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting The retinex theory of color vision

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.657986Z

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Observation 7c630e98-ffe2-4d5e-aa91-8f579c602b72 · outbound

This paper cites Lighting, reflectance and geometry estimation from 360 ◦ panoramic stereo, 2021.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Lighting, reflectance and geometry estimation from 360 ◦ panoramic stereo, 2021

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.643003Z

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Observation 62633d14-29f0-4c72-a6a6-6ad2e137f828 · outbound

This paper cites Learning intrinsic image de- composition from watching the world.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Learning intrinsic image de- composition from watching the world

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.627288Z

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Observation e61f2b4b-e289-45db-8a99-9b59aa7488c5 · outbound

This paper cites Physically-based editing of indoor scene lighting from a single image.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Physically-based editing of indoor scene lighting from a single image

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.609907Z

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Observation f14abfae-afdc-47b1-bd55-db3aa7afd1fb · outbound

This paper cites Multi-view inverse rendering for large-scale real- world indoor scenes, 2023.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Multi-view inverse rendering for large-scale real- world indoor scenes, 2023

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.594916Z

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Observation 841b1fe5-d7d7-4251-a28a-78959cb31933 · outbound

This paper cites Photorealistic object insertion with diffusion-guided inverse rendering.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Photorealistic object insertion with diffusion-guided inverse rendering

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.580106Z

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Observation 36aa467d-46bf-4bf3-8a3c-63380e19a387 · outbound

This paper cites Urbanir: Large-scale urban scene inverse ren- dering from a single video.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Urbanir: Large-scale urban scene inverse ren- dering from a single video

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.564554Z

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Observation 288fe395-ba3e-4065-a173-754d7b022d2c · outbound

This paper cites Learning to factorize and relight a city.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Learning to factorize and relight a city

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.549992Z

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Observation 867a8cec-1d05-4623-92d9-68631553de2a · outbound

This paper cites A convnet for the 2020s.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting A convnet for the 2020s

Reference 41

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Source-reported events for the cited work

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Observation 308f7819-c59d-41cc-b70d-7f36109b5afb · outbound

This paper cites Decoupled weight decay regularization.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Decoupled weight decay regularization

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.523936Z

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Observation 5b0860a3-27da-4ba1-8616-005ab5c02543 · outbound

This paper cites Intrinsicdiffusion: joint in- trinsic layers from latent diffusion models.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Intrinsicdiffusion: joint in- trinsic layers from latent diffusion models

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.508321Z

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Observation b9811a49-b288-4109-a98a-1c79836eb65e · outbound

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LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Unresolved cited work

Reference 44

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Observation bf248db4-3294-4a24-83e2-ae066a429f20 · outbound

This paper cites A multi-illumination dataset of indoor object ap- pearance.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting A multi-illumination dataset of indoor object ap- pearance

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.476402Z

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Observation b0d2f5bf-b4fc-47b7-a1ad-a957a506d079 · outbound

This paper cites Learning physics-guided face relighting under directional light.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Learning physics-guided face relighting under directional light

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.460216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 11c4531a-7c04-4b37-b633-b13dbec28396 · outbound

This paper cites Multi-view relighting using a geometry-aware network.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Multi-view relighting using a geometry-aware network

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.444440Z

Source-reported events for the cited work

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Observation 98091734-d918-4937-8f22-8159b3aad532 · outbound

This paper cites Diffusionlight: Light probes for free by painting a chrome ball.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Diffusionlight: Light probes for free by painting a chrome ball

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.428983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2bdd6970-0c96-4788-b6b8-b81d1c279e8d · outbound

This paper cites A Diffu- sion Approach to Radiance Field Relighting using Multi- Illumination Synthesis.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting A Diffu- sion Approach to Radiance Field Relighting using Multi- Illumination Synthesis

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.611616Z

Source-reported events for the cited work

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Observation 7da602e2-2265-490f-9deb-8cd0a572347e · outbound

This paper cites Difareli: Diffusion face relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Difareli: Diffusion face relighting

Reference 50

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Observation 5e88f6de-6073-46d9-98dc-3be7392ab516 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Learn- ing transferable visual models from natural language super- vision

Reference 51

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Observation 23cfaa84-e7ab-4199-9f66-25553b1d5255 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting High-resolution image syn- thesis with latent diffusion models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.373847Z

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Observation 4ed1658a-4d1c-43bc-8808-5cd4846adc46 · outbound

This paper cites Semantic image inversion and editing using rectified stochastic differential equations.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Semantic image inversion and editing using rectified stochastic differential equations

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.358761Z

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Observation a06fbde4-9b6b-487d-bd47-a0cf39ed9051 · outbound

This paper cites Nerf for outdoor scene relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Nerf for outdoor scene relighting

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.343764Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3782d135-22de-4530-9030-dfab17b5acfc · outbound

This paper cites Shadows don’t lie and lines can’t bend! generative models don’t know projective geometry.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Shadows don’t lie and lines can’t bend! generative models don’t know projective geometry

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.328898Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1eea0189-36c5-4b59-a0bc-024232301cae · outbound

This paper cites A light stage on every desk.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting A light stage on every desk

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.314553Z

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Observation 8e031755-381c-4962-9996-a9aebf64dbb3 · outbound

This paper cites Single image portrait relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Single image portrait relighting

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.299835Z

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Observation 803ababe-97d5-4c39-b8cb-34f46ad390e4 · outbound

This paper cites Relight my nerf: A dataset for novel view synthesis and re- lighting of real world objects.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Relight my nerf: A dataset for novel view synthesis and re- lighting of real world objects

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.285030Z

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Observation b28143d8-ac03-4c3c-93eb-67017293217c · outbound

This paper cites Zero-reference low-light enhancement via physical quadru- ple priors.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Zero-reference low-light enhancement via physical quadru- ple priors

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.269899Z

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Observation c9e7c011-8cea-4125-bccf-e6107cf90893 · outbound

This paper cites an unresolved cited work.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-12T05:46:07.254323Z

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Observation f0a9165f-4842-4799-9a87-ac7e257249d6 · outbound

This paper cites Intrinsic appearance decomposition using point cloud representation.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Intrinsic appearance decomposition using point cloud representation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.238854Z

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Observation a0a716a6-6c16-4600-a445-a267a4f8fccb · outbound

This paper cites Retinex-Diffusion: On Controlling Illumination Conditions in Diffusion Models via Retinex Theory.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Retinex-Diffusion: On Controlling Illumination Conditions in Diffusion Models via Retinex Theory

Reference 62

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Source-reported events for the cited work

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Observation 1c435a65-25cb-4171-8916-f7827eb79611 · outbound

This paper cites Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Good Seed Makes a Good Crop: Discovering Secret Seeds in Text-to-Image Diffusion Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.675442Z

Source-reported events for the cited work

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Observation 48fc0779-305c-456d-97f3-f7c38f585831 · outbound

This paper cites S3net: A single stream structure for depth guided image relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting S3net: A single stream structure for depth guided image relighting

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.222874Z

Source-reported events for the cited work

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Observation 6c85655e-71e2-441c-8104-7f9cb3c8d6cc · outbound

This paper cites LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.685004Z

Source-reported events for the cited work

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Observation 1e41a5c6-6efe-4d62-a473-2745cc976fa4 · outbound

This paper cites Self- supervised outdoor scene relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Self- supervised outdoor scene relighting

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.205422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4b8cc004-1e5a-4fed-b2dc-637dbddb74e0 · outbound

This paper cites Dilightnet: Fine-grained light- ing control for diffusion-based image generation.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Dilightnet: Fine-grained light- ing control for diffusion-based image generation

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.187803Z

Source-reported events for the cited work

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Observation 71aad605-0af9-4284-8c47-9063c2011858 · outbound

This paper cites Rgb-x: Image decomposition and synthesis using material-and lighting-aware diffusion models.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Rgb-x: Image decomposition and synthesis using material-and lighting-aware diffusion models

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.171522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 75bfa86d-3d41-47cf-aa29-082296811da5 · outbound

This paper cites Cohen, and Brian Curless.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Cohen, and Brian Curless

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.155558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7df7e25b-7649-4dbe-864f-a890f7da7a85 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Adding conditional control to text-to-image diffusion models

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.140088Z

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Observation 86235855-794f-44e0-b8b6-e417785d0cf5 · outbound

This paper cites Scaling in-the-wild training for diffusion-based illumination harmo- nization and editing by imposing consistent light transport.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Scaling in-the-wild training for diffusion-based illumination harmo- nization and editing by imposing consistent light transport

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.123669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c145331b-dd17-4150-b147-4cd4542590e8 · outbound

This paper cites Efros, Eli Shecht- man, and Oliver Wang.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Efros, Eli Shecht- man, and Oliver Wang

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.716784Z

Source-reported events for the cited work

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Observation 459b3f9a-ee37-40ba-9b28-192582b6e410 · outbound

This paper cites Neu- ral light transport for relighting and view synthesis.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Neu- ral light transport for relighting and view synthesis

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.097928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 929050f4-066e-4201-a23d-37177e19c423 · outbound

This paper cites Nerfac- tor: Neural factorization of shape and reflectance under an unknown illumination.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Nerfac- tor: Neural factorization of shape and reflectance under an unknown illumination

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.080224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d65c7446-77c2-4cac-b589-2ef746cb44f3 · outbound

This paper cites Latent intrinsics emerge from training to relight.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Latent intrinsics emerge from training to relight

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.064247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3e4281c7-4f51-4f2b-97d9-39501ca144ed · outbound

This paper cites ZeroComp: Zero-shot Object Compositing from Image Intrinsics via Diffusion.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting ZeroComp: Zero-shot Object Compositing from Image Intrinsics via Diffusion

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-12T05:46:06.735003Z

Source-reported events for the cited work

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Observation 8e92b5a2-01e0-49e9-8271-f54dda90e632 · outbound

This paper cites Srinivasan, Dor Verbin, Keunhong Park, Ricardo Martin Brualla, and Philipp Henzler.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Srinivasan, Dor Verbin, Keunhong Park, Ricardo Martin Brualla, and Philipp Henzler

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.048322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7c93be87-71c3-43b5-991f-6c397cee6dc6 · outbound

This paper cites Deep single-image portrait relighting.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting Deep single-image portrait relighting

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.031814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation bdb09493-3d6c-4411-ae45-b1072be69daf · outbound

This paper cites I 2-sdf: Intrinsic indoor scene reconstruction and editing via raytracing in neural sdfs, 2023.

LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting I 2-sdf: Intrinsic indoor scene reconstruction and editing via raytracing in neural sdfs, 2023

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:46:07.016547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

Observation 6e9dc0be-a7f6-48e5-b690-bac02ac785a3 · inbound

MV-CoLight: Efficient Object Compositing with Consistent Lighting and Shadow Generation cites this paper.

MV-CoLight: Efficient Object Compositing with Consistent Lighting and Shadow Generation LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T13:35:50.655346Z

Source-reported events for the cited work

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Observation 0ed1feba-14a3-4f64-b15d-3608446f5304 · inbound

TRON: Tracing Rays to Orchestrate a Neural Renderer for 3D Gaussian Reconstructions cites this paper.

TRON: Tracing Rays to Orchestrate a Neural Renderer for 3D Gaussian Reconstructions LumiNet: Latent Intrinsics Meets Diffusion Models for Indoor Scene Relighting

Reference 96

Resolution: verified exact; arxiv_id, observed 2026-07-03T05:07:38.802773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.