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Paper Citation Record · LEDGER

AI-powered Contextual 3D Environment Generation: A Systematic Review

As of 8 August 2026, this Paper Citation Record lists 100 of 123 outbound references and 0 inbound Pith citation observations for arXiv:2506.05449.

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

pith.paper-citation-record.v1
2506.05449 v1

Coverage vector

measured 100 of 123 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:29:43.992088Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

100 of 123 outbound references displayed

  • verified exact15
  • verified fuzzy0
  • unresolved65
  • parse uncertain0
  • malformed identifier18
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 45b1efc5-f414-4a68-8644-e483a250715e · outbound

This paper cites A survey on procedural modelling for virtual worlds.

AI-powered Contextual 3D Environment Generation: A Systematic Review A survey on procedural modelling for virtual worlds

Reference 1

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Observation d1dc12f8-665a-45c3-99c8-84a172bfeed7 · outbound

This paper cites Deep learning- based 3D reconstruction: a survey.

AI-powered Contextual 3D Environment Generation: A Systematic Review Deep learning- based 3D reconstruction: a survey

Reference 2

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Observation ea9acebb-36f1-4a05-8db5-58ef41e20d8e · outbound

This paper cites Procedural content generation via machine learning (PCGML).

AI-powered Contextual 3D Environment Generation: A Systematic Review Procedural content generation via machine learning (PCGML)

Reference 3

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Observation 81a2a7ae-c2f0-485d-a4ec-f0fe7b23a981 · outbound

This paper cites 3D-LLM: Injecting the 3D World into Large Language Models.

AI-powered Contextual 3D Environment Generation: A Systematic Review 3D-LLM: Injecting the 3D World into Large Language Models

Reference 4

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source=pdf_text observed=2026-08-07T10:29:07.913635Z digest=sha256:1bec586c557cee149e5588f3a5eb9f8d56a588c75e683a322b8843d0710d1801

Observation aa88b9f5-a601-43bd-98df-2918033f6ece · outbound

This paper cites Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models.

AI-powered Contextual 3D Environment Generation: A Systematic Review Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models

Reference 5

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source=pdf_text observed=2026-08-07T10:29:07.974786Z digest=sha256:1047879782cd2858a789a7aaddb09bfa01ff054fea2858d919438898b7c99ebb

Observation 39be8cc0-e430-4709-8894-2b7bad1c3b7c · outbound

This paper cites RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion.

AI-powered Contextual 3D Environment Generation: A Systematic Review RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion

Reference 6

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Observation 09cb3e0e-1c2c-4abb-9260-ea8e6ba87747 · outbound

This paper cites The PRISMA 2020 statement: an updated guideline for reporting systematic reviews.

AI-powered Contextual 3D Environment Generation: A Systematic Review The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

Reference 7

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source=pdf_text observed=2026-08-07T10:29:08.137297Z digest=sha256:43def52a5095219548dac8a95443b3d87155adb56beac78269346777d761a869

Observation 3d152b19-e717-49a7-9301-978118265314 · outbound

This paper cites Edify 3D: Scalable High-Quality 3D Asset Generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review Edify 3D: Scalable High-Quality 3D Asset Generation

Reference 8

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source=pdf_text observed=2026-08-07T10:29:08.203676Z digest=sha256:38de2be58905bebffbb70ee1c774feeb50708df3944267d77e2f1babfaa06a3f

Observation dd39bbcf-ae98-4c7f-b5b4-3337419ff97f · outbound

This paper cites NeRF-IS: Explicit Neural Radi- ance Fields in Semantic Space.

AI-powered Contextual 3D Environment Generation: A Systematic Review NeRF-IS: Explicit Neural Radi- ance Fields in Semantic Space

Reference 10

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Observation a1996653-12e7-4f5b-8244-079a2f44fa58 · outbound

This paper cites V AIDE: Virtual AI Designer for Web3D Exhibition Layout Creation.

AI-powered Contextual 3D Environment Generation: A Systematic Review V AIDE: Virtual AI Designer for Web3D Exhibition Layout Creation

Reference 11

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source=pdf_text observed=2026-08-07T10:29:08.423938Z digest=sha256:a86183d7a59fe33f53ea22c3d03cf41f5e6ae9a75ee831f868eac101b7928f64

Observation e2383a6c-a368-4e2a-a409-0d6436dd117d · outbound

This paper cites SPAGHETTI: editing implicit shapes through part aware generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review SPAGHETTI: editing implicit shapes through part aware generation

Reference 12

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Observation 549e0873-4414-42c3-98a0-8f3d6a47b7ba · outbound

This paper cites Generative Terrain Authoring with Mid-air Hand Sketching in Virtual Reality.

AI-powered Contextual 3D Environment Generation: A Systematic Review Generative Terrain Authoring with Mid-air Hand Sketching in Virtual Reality

Reference 13

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Observation 1cfb5eed-96e9-4cf6-b02a-dc9ecd0dd809 · outbound

This paper cites SP-GAN: sphere-guided 3D shape generation and manipulation.

AI-powered Contextual 3D Environment Generation: A Systematic Review SP-GAN: sphere-guided 3D shape generation and manipulation

Reference 14

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Observation af7325ec-571f-4026-9b35-346d7e64d32d · outbound

This paper cites Creating and Experiencin 3D Im- mersion Using Generative 2D Diffusion: An Integrated Framework.

AI-powered Contextual 3D Environment Generation: A Systematic Review Creating and Experiencin 3D Im- mersion Using Generative 2D Diffusion: An Integrated Framework

Reference 16

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source=pdf_text observed=2026-08-07T10:29:08.831058Z digest=sha256:a989be949778f704a6194c5132f3f2af8aa1385c1f3f26805982aaa750bc47c6

Observation 6f7cc042-a43b-44b5-8245-582c9f7c915c · outbound

This paper cites LLMR: Real-time Prompting of Interactive Worlds using Large Language Models.

AI-powered Contextual 3D Environment Generation: A Systematic Review LLMR: Real-time Prompting of Interactive Worlds using Large Language Models

Reference 17

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source=pdf_text observed=2026-08-07T10:29:09.058381Z digest=sha256:3b9c6df94cd22a9ca4f2dc2a4a235dfc05cb4b28b010ff500febe83ce75befbc

Observation 54a07cf4-0b60-4a76-bb16-290bc62e9623 · outbound

This paper cites NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Mod- els.

AI-powered Contextual 3D Environment Generation: A Systematic Review NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Mod- els

Reference 18

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source=pdf_text observed=2026-08-07T10:29:09.281993Z digest=sha256:3eebe3ba61c1a2e84abadc4da63c806ed80cab187847f300c03010e09fec3c36

Observation 1d7d0bc8-afea-4031-a9b4-35e9c5549c8b · outbound

This paper cites SceneHGN: Hierarchical Graph Net- works for 3D Indoor Scene Generation With Fine- Grained Geometry.

AI-powered Contextual 3D Environment Generation: A Systematic Review SceneHGN: Hierarchical Graph Net- works for 3D Indoor Scene Generation With Fine- Grained Geometry

Reference 22

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source=pdf_text observed=2026-08-07T10:29:09.750551Z digest=sha256:ee03670cee9bfdb5451193e7b0c0f07def7e7ff860b2dcab0b2f13c83fb7f630

Observation bda1a2fd-4a9d-4d74-a44c-92c597ccfd3d · outbound

This paper cites iControl3D: An Interactive System for Controllable 3D Scene Generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review iControl3D: An Interactive System for Controllable 3D Scene Generation

Reference 24

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Observation 121bcb83-08fa-4f99-a379-a55b6aefcdbd · outbound

This paper cites MemoVis: A GenAI-Powered Tool for Creating Companion Reference Images for 3D Design Feedback.

AI-powered Contextual 3D Environment Generation: A Systematic Review MemoVis: A GenAI-Powered Tool for Creating Companion Reference Images for 3D Design Feedback

Reference 25

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 68abad83-ef73-4eca-81d3-a0510076f892 · outbound

This paper cites ProteusNeRF: Fast Lightweight NeRF Editing using 3D-Aware Image Context.

AI-powered Contextual 3D Environment Generation: A Systematic Review ProteusNeRF: Fast Lightweight NeRF Editing using 3D-Aware Image Context

Reference 26

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Observation f820ea7d-9d3b-453d-9575-b11e8dc39647 · outbound

This paper cites A Multi-Stage Advanced Deep Learning Graphics Pipeline.

AI-powered Contextual 3D Environment Generation: A Systematic Review A Multi-Stage Advanced Deep Learning Graphics Pipeline

Reference 28

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Observation 73a5ec03-3325-4d38-8140-7782bee940b3 · outbound

This paper cites A Survey on Generative Adversarial Networks: Variants, Appli- cations, and Training.

AI-powered Contextual 3D Environment Generation: A Systematic Review A Survey on Generative Adversarial Networks: Variants, Appli- cations, and Training

Reference 30

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 740bfc98-8aa9-48c4-a7cc-3d6522c8545c · outbound

This paper cites A Neural Space-Time Represen- tation for Text-to-Image Personalization.

AI-powered Contextual 3D Environment Generation: A Systematic Review A Neural Space-Time Represen- tation for Text-to-Image Personalization

Reference 33

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source=pdf_text observed=2026-08-07T10:29:10.500170Z digest=sha256:54a44c6432c7f96eb2285d5ede11b93ac9a1d7429abfdffa3a76158ecee809c6

Observation 78db6bc9-0065-4c6c-a2c8-bb81476dc0f0 · outbound

This paper cites Artin- ter: AI-powered Boundary Objects for Commission- ing Visual Arts.

AI-powered Contextual 3D Environment Generation: A Systematic Review Artin- ter: AI-powered Boundary Objects for Commission- ing Visual Arts

Reference 34

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Observation 680f8b81-b711-4d36-bdfa-76bc8e20cd2d · outbound

This paper cites Autoencoder-Based Collaborative Attention GAN for Multi-Modal Image Synthesis.

AI-powered Contextual 3D Environment Generation: A Systematic Review Autoencoder-Based Collaborative Attention GAN for Multi-Modal Image Synthesis

Reference 35

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Observation f2e10cd7-1f0f-432d-8909-3c03b2a911c6 · outbound

This paper cites FIND: Fine-tuning Initial Noise Distribution with Policy Optimization for Diffusion Models.

AI-powered Contextual 3D Environment Generation: A Systematic Review FIND: Fine-tuning Initial Noise Distribution with Policy Optimization for Diffusion Models

Reference 36

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source=pdf_text observed=2026-08-07T10:29:10.742138Z digest=sha256:e28dd3458e1f7dc1e1ed3f4879e68a2d5d2a0205baad915e8114ff39a5b27a7b

Observation eb5fb1f9-8ab0-4006-8a05-3b2a1db1ee4e · outbound

This paper cites ConceptLab: Creative Concept Generation using VLM-Guided Diffusion Prior Con- straints.

AI-powered Contextual 3D Environment Generation: A Systematic Review ConceptLab: Creative Concept Generation using VLM-Guided Diffusion Prior Con- straints

Reference 37

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:10.828750Z digest=sha256:f0babcdb579a42f869345213fdb3e60176f8087ae2ef2e902e0df8530b926d3a

Observation 8859a2a6-cd49-4994-b72c-2594e9df32d9 · outbound

This paper cites GeoLatent: A Geometric Approach to Latent Space Design for Deformable Shape Gen- erators.

AI-powered Contextual 3D Environment Generation: A Systematic Review GeoLatent: A Geometric Approach to Latent Space Design for Deformable Shape Gen- erators

Reference 38

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source=pdf_text observed=2026-08-07T10:29:10.910883Z digest=sha256:28d1397411f475167f489d5dd2571fc2ab4d20d39f2cc61d38e96f4914f0b59f

Observation 74cccdcf-238a-4c2e-bb75-9fc7a1c15d10 · outbound

This paper cites Sat2Scene: 3D Urban Scene Gen- eration from Satellite Images with Diffusion.

AI-powered Contextual 3D Environment Generation: A Systematic Review Sat2Scene: 3D Urban Scene Gen- eration from Satellite Images with Diffusion

Reference 39

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source=pdf_text observed=2026-08-07T10:29:10.977219Z digest=sha256:02038477305af41ed41c284673abf66b91519de753df901dfae710a176054878

Observation 02c9f01b-a7af-4283-a22a-9aec7fd366db · outbound

This paper cites Synthesizing Indoor Scene Layouts in Complicated Architecture Using Dynamic Convolution Networks.

AI-powered Contextual 3D Environment Generation: A Systematic Review Synthesizing Indoor Scene Layouts in Complicated Architecture Using Dynamic Convolution Networks

Reference 40

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source=pdf_text observed=2026-08-07T10:29:11.049907Z digest=sha256:28d712af94bfdd651934ff133c479827c3388ac3e06e458450604bd57ac3a612

Observation 13cda361-1a14-4c17-b1bf-283b19683a4f · outbound

This paper cites DG3D: Generating High Quality 3D Textured Shapes by Learning to Discriminate Multi- Modal Diffusion-Renderings.

AI-powered Contextual 3D Environment Generation: A Systematic Review DG3D: Generating High Quality 3D Textured Shapes by Learning to Discriminate Multi- Modal Diffusion-Renderings

Reference 41

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source=pdf_text observed=2026-08-07T10:29:11.114215Z digest=sha256:edbe0420ff2234c4111cba12953e58c99b41ddae2243f7b2bdf52bd859f1f112

Observation 6f3c217b-fee6-4f08-8b2e-c9e54f348ebb · outbound

This paper cites 3DP3: 3D Scene Perception via Probabilistic Programming.

AI-powered Contextual 3D Environment Generation: A Systematic Review 3DP3: 3D Scene Perception via Probabilistic Programming

Reference 42

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source=pdf_text observed=2026-08-07T10:29:42.469348Z digest=sha256:ab8a16f66218339b69da8ef86a58fec3e64f524c8f642e4dac0cb1b875a85173

Observation db8dbe5e-30c6-41e5-8d33-92333ec49a12 · outbound

This paper cites Sparse Query Dense: Enhanc- ing 3D Object Detection with Pseudo Points.

AI-powered Contextual 3D Environment Generation: A Systematic Review Sparse Query Dense: Enhanc- ing 3D Object Detection with Pseudo Points

Reference 43

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source=pdf_text observed=2026-08-07T10:29:42.512750Z digest=sha256:93662270e1e6e21560d64a85c4d4f35bf2799f9f0ab2eed41b9c64dea4231798

Observation 14dbdb53-e885-45db-a344-353e1b88bcfa · outbound

This paper cites rlty2rlty: Transitioning Between Realities with Gen- erative AI.

AI-powered Contextual 3D Environment Generation: A Systematic Review rlty2rlty: Transitioning Between Realities with Gen- erative AI

Reference 46

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source=pdf_text observed=2026-08-07T10:29:42.738897Z digest=sha256:db4cefb5356fd4810534c1d0ed50c54b53c1b4ee432353e4e14dba49a198f93d

Observation 1b94db70-ab8e-42c6-8812-4fd481aac915 · outbound

This paper cites SinGRAF: Learning a 3D Gen- erative Radiance Field for a Single Scene.

AI-powered Contextual 3D Environment Generation: A Systematic Review SinGRAF: Learning a 3D Gen- erative Radiance Field for a Single Scene

Reference 48

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:42.846142Z digest=sha256:da1a3325310075c1a73a1c8ad7451aa371c63754ee75d9508368801d8e73024c

Observation ddb8f1bb-a425-4599-b8f8-f1cec4cd9f3a · outbound

This paper cites RIP-NeRF: Learning Rotation- Invariant Point-based Neural Radiance Field for Fine- grained Editing and Compositing.

AI-powered Contextual 3D Environment Generation: A Systematic Review RIP-NeRF: Learning Rotation- Invariant Point-based Neural Radiance Field for Fine- grained Editing and Compositing

Reference 49

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:29:42.916512Z digest=sha256:f16e7b3e28886ad5d628d4b75592947c7ee202ace96ee0f4de74856a09b24ea3

Observation a7478d4a-bc67-45f7-a155-c6ed453d699d · outbound

This paper cites In- teractive Latent Variable Evolution for the Generation of Minecraft Structures.

AI-powered Contextual 3D Environment Generation: A Systematic Review In- teractive Latent Variable Evolution for the Generation of Minecraft Structures

Reference 50

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source=pdf_text observed=2026-08-07T10:29:42.990589Z digest=sha256:ab8e7bde7c030afbd4e010521014eeef944db951eeb91d669a17da50b6aad704

Observation 7d552ec0-cf32-462f-8098-ddcf94b78114 · outbound

This paper cites World-GAN: a Generative Model for Minecraft Worlds.

AI-powered Contextual 3D Environment Generation: A Systematic Review World-GAN: a Generative Model for Minecraft Worlds

Reference 51

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source=pdf_text observed=2026-08-07T10:29:43.059376Z digest=sha256:d40e61bb9777dee30cf46fb4c333fcafb5c86ebcc00f4443739d5dfa858e022a

Observation 786f7a51-a8f2-494b-a4d2-92b14dc725e2 · outbound

This paper cites CLIP-Mesh: Generat- ing textured meshes from text using pretrained image- text models.

AI-powered Contextual 3D Environment Generation: A Systematic Review CLIP-Mesh: Generat- ing textured meshes from text using pretrained image- text models

Reference 53

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source=pdf_text observed=2026-08-07T10:29:43.133049Z digest=sha256:efe8642ab96339b978bea2b92aad032354fe14701d1f3869080b1c7a83d05560

Observation 70ac4a88-426a-4ee0-b6ae-9f76c5ec0258 · outbound

This paper cites VRCopilot: Authoring 3D Layouts with Generative AI Models in VR.

AI-powered Contextual 3D Environment Generation: A Systematic Review VRCopilot: Authoring 3D Layouts with Generative AI Models in VR

Reference 54

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source=pdf_text observed=2026-08-07T10:29:43.256820Z digest=sha256:d2489b10c086ba5bb040db996da9511b80e15a6af559770c8f7a8df54372ec12

Observation 1681b52c-3082-4a37-8abe-33e6004c9211 · outbound

This paper cites WorldSmith: Iterative and Expressive Prompting for World Building with a Generative AI.

AI-powered Contextual 3D Environment Generation: A Systematic Review WorldSmith: Iterative and Expressive Prompting for World Building with a Generative AI

Reference 55

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source=pdf_text observed=2026-08-07T10:29:43.313382Z digest=sha256:890c8213dbde90ddb905a667a3d0e260e81c810b80d85ea8cc517345d40710d7

Observation 87c66b33-add0-4c76-8ca8-ed8c57257fb5 · outbound

This paper cites Generating and Integrating Dif- fusion Model-Based Panoramic Views for Virtual In- terview Platform.

AI-powered Contextual 3D Environment Generation: A Systematic Review Generating and Integrating Dif- fusion Model-Based Panoramic Views for Virtual In- terview Platform

Reference 56

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.397955Z digest=sha256:ec0aeceb4226307154f929e1ad8cd821656f9b89145c70b3ad1253e90034b0c4

Observation a4247c26-b94f-4653-b3ad-7c69700c33bb · outbound

This paper cites BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane Extrapola- tion.

AI-powered Contextual 3D Environment Generation: A Systematic Review BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane Extrapola- tion

Reference 58

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source=pdf_text observed=2026-08-07T10:29:43.421032Z digest=sha256:d9afa2683a82d246991e6b168e2d260abf96e7be4516282ad02b566e25a5fba2

Observation 6c7f086d-0d57-4b36-944c-2a66e2bb5b25 · outbound

This paper cites L-MAGIC: Language Model As- sisted Generation of Images with Coherence.

AI-powered Contextual 3D Environment Generation: A Systematic Review L-MAGIC: Language Model As- sisted Generation of Images with Coherence

Reference 59

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.437207Z digest=sha256:e04cb10aeb4d21377ab1cdacb61f2d420e8ebfb4ac5373fb31982f361670a77f

Observation 4d7cc215-bcb9-469f-8a27-d1d1ddb8dd25 · outbound

This paper cites iNVS: Repurposing Diffusion In- painters for Novel View Synthesis.

AI-powered Contextual 3D Environment Generation: A Systematic Review iNVS: Repurposing Diffusion In- painters for Novel View Synthesis

Reference 60

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source=pdf_text observed=2026-08-07T10:29:43.452421Z digest=sha256:de1094c4d08e02ecb1b9d0a6d2ec206659c2f25c75388ea44e53f91ac3c8bd9a

Observation c914225a-3526-42e1-9cc6-063ec8565793 · outbound

This paper cites WorldGen: A Large Scale Generative Simulator.

AI-powered Contextual 3D Environment Generation: A Systematic Review WorldGen: A Large Scale Generative Simulator

Reference 61

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source=pdf_text observed=2026-08-07T10:29:43.467084Z digest=sha256:4157a493c91aa5671fefae2db7ad377b827d2f79160d4368df0668c8df2d9132

Observation 80e94ce1-f1a9-4f05-b075-18811f34f12a · outbound

This paper cites ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives.

AI-powered Contextual 3D Environment Generation: A Systematic Review ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives

Reference 62

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.477441Z digest=sha256:9d79c09d4eb6333adee28d85758b7f59ae4f4334b4f9646ec48eac2c60e90fce

Observation 6a92cdea-a5d1-41de-80c2-b7a24bd74ce9 · outbound

This paper cites Assessing the Utility of GAN-Generated 3D Virtual Desert Terrain: A User- Centric Evaluation of Immersion and Realism.

AI-powered Contextual 3D Environment Generation: A Systematic Review Assessing the Utility of GAN-Generated 3D Virtual Desert Terrain: A User- Centric Evaluation of Immersion and Realism

Reference 63

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source=pdf_text observed=2026-08-07T10:29:43.486597Z digest=sha256:6cc45bb01ccaaf38edcd404c30e9301247ba800d1eb52a407cddc50d777a0d48

Observation 16453975-fe61-494a-9986-6c941369b8c8 · outbound

This paper cites LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer.

AI-powered Contextual 3D Environment Generation: A Systematic Review LART: Neural Correspondence Learning with Latent Regularization Transformer for 3D Motion Transfer

Reference 65

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source=pdf_text observed=2026-08-07T10:29:43.504072Z digest=sha256:672bca00c6bf423be4957bd1e5f0b807bffbbfb8009abe889e5344a5bdbab6b2

Observation 478c7034-57de-40c8-ac20-2acd143c8b12 · outbound

This paper cites DreamUp3D: Object-Centric Genera- tive Models for Single-View 3D Scene Understanding and Real-to-Sim Transfer.

AI-powered Contextual 3D Environment Generation: A Systematic Review DreamUp3D: Object-Centric Genera- tive Models for Single-View 3D Scene Understanding and Real-to-Sim Transfer

Reference 66

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source=pdf_text observed=2026-08-07T10:29:43.515389Z digest=sha256:3944166da6c9e1a3f5044d57e1563f66a93a1f9166c7931436d4b25b63214f62

Observation 290be1b0-a510-47b9-bb96-01d1d2ae3a18 · outbound

This paper cites CLAY: A Controllable Large- scale Generative Model for Creating High-quality 3D Assets.

AI-powered Contextual 3D Environment Generation: A Systematic Review CLAY: A Controllable Large- scale Generative Model for Creating High-quality 3D Assets

Reference 67

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source=pdf_text observed=2026-08-07T10:29:43.527148Z digest=sha256:db518dd17210164d1233738e66bf5ff57d6c341861edb92acacc4370474017bc

Observation 1770a69b-a09f-41cf-91fe-be151ef236d8 · outbound

This paper cites MultiCAD: Contrastive Represen- tation Learning for Multi-modal 3D Computer-Aided Design Models.

AI-powered Contextual 3D Environment Generation: A Systematic Review MultiCAD: Contrastive Represen- tation Learning for Multi-modal 3D Computer-Aided Design Models

Reference 68

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source=pdf_text observed=2026-08-07T10:29:43.535734Z digest=sha256:107b90f19bc11a494d3759f623bc20922bf116fc34f42e6fce1c35fd42fe6ee3

Observation d0842b1c-8c00-4116-a87b-0ce74bb6ed0d · outbound

This paper cites 360° Reconstruction From a Single Image Using Space Carved Outpainting.

AI-powered Contextual 3D Environment Generation: A Systematic Review 360° Reconstruction From a Single Image Using Space Carved Outpainting

Reference 70

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source=pdf_text observed=2026-08-07T10:29:43.560477Z digest=sha256:5f463f2b59a209a4d94dcac51c7bce43d1a6d0726ec45599e8e6d5cb4301acfc

Observation cb373103-e95e-4777-9b84-9ad3a97eddf3 · outbound

This paper cites Cross-modal 3D Shape Gener- ation and Manipulation.

AI-powered Contextual 3D Environment Generation: A Systematic Review Cross-modal 3D Shape Gener- ation and Manipulation

Reference 71

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source=pdf_text observed=2026-08-07T10:29:43.570880Z digest=sha256:5b5c4ff8e87d81f79cde6edb9bb59799619b8b8a49663966446c6cdca26ea414

Observation acf5f2bd-b050-4957-a69e-ad2dcdcbf757 · outbound

This paper cites ChartPointFlow for Topology-Aware 3D Point Cloud Generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review ChartPointFlow for Topology-Aware 3D Point Cloud Generation

Reference 72

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no resolver link, observed 2026-08-07T10:29:43.580751Z

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source=pdf_text observed=2026-08-07T10:29:43.580751Z digest=sha256:1336baeb99abd50395ce7addd11dc94fd0ee5218c7e561e638bddeeb1e5b9c90

Observation 9ea0fa19-3c50-47e2-b763-bbd9f43f57f2 · outbound

This paper cites Elevating Perception: Unified Recognition Framework and Vision-Language Pre- Training Using Three-Dimensional Image Reconstruc- tion.

AI-powered Contextual 3D Environment Generation: A Systematic Review Elevating Perception: Unified Recognition Framework and Vision-Language Pre- Training Using Three-Dimensional Image Reconstruc- tion

Reference 74

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source=pdf_text observed=2026-08-07T10:29:43.602257Z digest=sha256:4b0b510c2deedf664d34f3b0cb8310e518e2cfa48222fa039b4639525687801e

Observation 0bfbe79a-4985-48a4-ae94-df923241f637 · outbound

This paper cites Self-Supervised Learning on 3D Point Clouds by Learning Discrete Generative Models.

AI-powered Contextual 3D Environment Generation: A Systematic Review Self-Supervised Learning on 3D Point Clouds by Learning Discrete Generative Models

Reference 75

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source=pdf_text observed=2026-08-07T10:29:43.611623Z digest=sha256:dc9f32aeb4c318a102d201a24a829d8b514130156a26376b6cc45b6ea6de8e29

Observation c191d884-a6d5-4341-b21c-b76bae27497d · outbound

This paper cites EASI-Tex: Edge-Aware Mesh Texturing from Single Image.

AI-powered Contextual 3D Environment Generation: A Systematic Review EASI-Tex: Edge-Aware Mesh Texturing from Single Image

Reference 76

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verified exact
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.621763Z digest=sha256:6ebb1d5266c221452f4d1049419f27ae523eba862c84c042d389c12dba26be77

Observation 336fe3c0-29e8-4fcb-a127-2c02f241e289 · outbound

This paper cites F-3DGS: Factorized Coordinates and Representations for 3D Gaussian Splatting.

AI-powered Contextual 3D Environment Generation: A Systematic Review F-3DGS: Factorized Coordinates and Representations for 3D Gaussian Splatting

Reference 77

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source=pdf_text observed=2026-08-07T10:29:43.634131Z digest=sha256:55e31932026482fd1841cdca2c6487ebf987ae93f9fbf39ae3c8b3e1350ea036

Observation 800757f9-3f95-4422-9a51-35b2f246bc5b · outbound

This paper cites 3DShape2VecSet: A 3D Shape Rep- resentation for Neural Fields and Generative Diffusion Models.

AI-powered Contextual 3D Environment Generation: A Systematic Review 3DShape2VecSet: A 3D Shape Rep- resentation for Neural Fields and Generative Diffusion Models

Reference 78

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source=pdf_text observed=2026-08-07T10:29:43.646976Z digest=sha256:eb2365b94a27ee1e2dd06addb31ad49acc4d88f7066986e29d3d75e0648cf36a

Observation 5dfbae4d-e6e6-4b82-9b1f-1cf3f65693b3 · outbound

This paper cites HyperDreamer: Hyper-Realistic 3D Content Generation and Editing from a Single Image.

AI-powered Contextual 3D Environment Generation: A Systematic Review HyperDreamer: Hyper-Realistic 3D Content Generation and Editing from a Single Image

Reference 79

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source=pdf_text observed=2026-08-07T10:29:43.656099Z digest=sha256:e35d6ba459ea11dc7b134466b9002ea210971991a227b23b23e2d1629c8ff999

Observation 84126f76-fe78-4b0a-b3f2-46c3b3803496 · outbound

This paper cites An End-to-End Conditional Generative Adversarial Network Based on Depth Map for 3D Craniofacial Reconstruction.

AI-powered Contextual 3D Environment Generation: A Systematic Review An End-to-End Conditional Generative Adversarial Network Based on Depth Map for 3D Craniofacial Reconstruction

Reference 80

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source=pdf_text observed=2026-08-07T10:29:43.665778Z digest=sha256:108a4b8c22d0b2ad6399e590f1fbd9f16292784f65b51809472940024d6b5522

Observation 2893f613-324e-4c72-8d3d-68cb44679ef0 · outbound

This paper cites Object-centric Learning with Capsule Networks: A Survey.

AI-powered Contextual 3D Environment Generation: A Systematic Review Object-centric Learning with Capsule Networks: A Survey

Reference 81

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source=pdf_text observed=2026-08-07T10:29:43.678151Z digest=sha256:f6566e7df203ef36bfebe1a52794856dca09dabe2f22c6bf3defa9431d94e191

Observation b88f2a24-19d3-412b-b0d1-83a5d1b41d4e · outbound

This paper cites Learning to Gen- erate 3D Shapes from a Single Example.

AI-powered Contextual 3D Environment Generation: A Systematic Review Learning to Gen- erate 3D Shapes from a Single Example

Reference 82

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source=pdf_text observed=2026-08-07T10:29:43.691586Z digest=sha256:7cd2d1e97ee2eab6fabfb5f2b53f002c0a58ab6571f61fee1aa3fa55b108684d

Observation e77d4f67-53db-4897-afd5-caad8340285d · outbound

This paper cites Text-Free Controllable 3-D Point Cloud Generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review Text-Free Controllable 3-D Point Cloud Generation

Reference 83

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.700867Z digest=sha256:af6073f94d6053f15060ed98c98b8879e75c1c9401e43dbfbd2d080b05db5c68

Observation 71d483b7-6a85-46dc-aee0-6a48e14242bd · outbound

This paper cites A Study on V oxel Shape Generation and Reconstruction with VQ-V AE- 2.

AI-powered Contextual 3D Environment Generation: A Systematic Review A Study on V oxel Shape Generation and Reconstruction with VQ-V AE- 2

Reference 84

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metadata mismatch
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.712357Z digest=sha256:60282bfcc806bc69b2ed588246a758f88048176ace8a51c995100b9ac548a4b6

Observation b1eedd0c-b4af-4007-9555-39803a53ff77 · outbound

This paper cites Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowl- edge Distillation.

AI-powered Contextual 3D Environment Generation: A Systematic Review Embracing the Dark Knowledge: Domain Generalization Using Regularized Knowl- edge Distillation

Reference 85

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source=pdf_text observed=2026-08-07T10:29:43.725171Z digest=sha256:8a7ab9bedad98024c741794bf896ea53e281da15d7f675516683eb9835ec3f4f

Observation db81ada3-9e58-4887-84b0-b4db1f7f59b0 · outbound

This paper cites Text-to-3D Generative AI on Mobile Devices: Measurements and Optimizations.

AI-powered Contextual 3D Environment Generation: A Systematic Review Text-to-3D Generative AI on Mobile Devices: Measurements and Optimizations

Reference 90

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source=pdf_text observed=2026-08-07T10:29:43.776166Z digest=sha256:45d31ea6b1af25c55afd31c46b79952b367f8bc41f9e4c4df04f184753154c88

Observation 54cb3510-df53-41fe-ae1e-d0c3196b07ac · outbound

This paper cites RelScene: A Benchmark and base- line for Spatial Relations in text-driven 3D Scene Generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review RelScene: A Benchmark and base- line for Spatial Relations in text-driven 3D Scene Generation

Reference 91

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source=pdf_text observed=2026-08-07T10:29:43.785182Z digest=sha256:cf3be7c3623c13041d4816b484218fc2a925e67b775f566915d4c77d8278b917

Observation ef93d9ee-0595-4bac-a01b-ca985c2199ec · outbound

This paper cites CAD Translator: An Effective Drive for Text to 3D Parametric Computer-Aided Design Generative Modeling.

AI-powered Contextual 3D Environment Generation: A Systematic Review CAD Translator: An Effective Drive for Text to 3D Parametric Computer-Aided Design Generative Modeling

Reference 92

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source=pdf_text observed=2026-08-07T10:29:43.794221Z digest=sha256:d86189d2800f347440ce90e6c457ed5710f60c95a8f6688c85c5bfd149b3802b

Observation 482e22ac-82a7-460a-aad6-b72d4a628555 · outbound

This paper cites ImageBind3D: Image as Binding Step for Controllable 3D Generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review ImageBind3D: Image as Binding Step for Controllable 3D Generation

Reference 93

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source=pdf_text observed=2026-08-07T10:29:43.802716Z digest=sha256:4a6611662acff24af09671db5312f82823f0bf9f012d45c4c1d6d0f102085144

Observation 12bfaba7-eac9-42b8-8b34-d3ed130ef188 · outbound

This paper cites DreamLCM: Towards High Quality Text-to-3D Generation via Latent Consistency Model.

AI-powered Contextual 3D Environment Generation: A Systematic Review DreamLCM: Towards High Quality Text-to-3D Generation via Latent Consistency Model

Reference 94

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source=pdf_text observed=2026-08-07T10:29:43.821107Z digest=sha256:1c3a781c4d7e7b6595ae72e5ac376c205b55903a3db406c2031f3d81f4f0657e

Observation 9e9c75ae-e6d4-4ec6-b244-53af6d61a229 · outbound

This paper cites Dream Mesh: A Speech-to-3D Model Generative Pipeline in Mixed Reality.

AI-powered Contextual 3D Environment Generation: A Systematic Review Dream Mesh: A Speech-to-3D Model Generative Pipeline in Mixed Reality

Reference 95

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source=pdf_text observed=2026-08-07T10:29:43.826519Z digest=sha256:7e38d604e69863300d641686d56f13849c57a3051edab26fd8c25db2336880bd

Observation cc4ae632-c20b-4038-a558-2efcb008b305 · outbound

This paper cites PlacidDreamer: Advancing Har- mony in Text-to-3D Generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review PlacidDreamer: Advancing Har- mony in Text-to-3D Generation

Reference 96

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source=pdf_text observed=2026-08-07T10:29:43.843820Z digest=sha256:79f0933b47cd6d26ada6d372777f8cf5bbb899f3093320d98a095c0417af3829

Observation 7a9e00be-e4ab-4b6d-a1c6-2b5c0c606d15 · outbound

This paper cites Text2VRScene: Exploring the Framework of Automated Text-driven Generation Sys- tem for VR Experience.

AI-powered Contextual 3D Environment Generation: A Systematic Review Text2VRScene: Exploring the Framework of Automated Text-driven Generation Sys- tem for VR Experience

Reference 97

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source=pdf_text observed=2026-08-07T10:29:43.852572Z digest=sha256:f609e804554d1878d514c4a43468cf009bf84c1d5c6ad84974010d3f18436ca9

Observation 769f4295-9bda-4857-a8bd-7471879cc17f · outbound

This paper cites Prompt Engineering for X3D Object Creation with LLMs.

AI-powered Contextual 3D Environment Generation: A Systematic Review Prompt Engineering for X3D Object Creation with LLMs

Reference 98

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source=pdf_text observed=2026-08-07T10:29:43.861458Z digest=sha256:b810599f4ddd86ced7fef0c91da7a6843722e3b923450ce387c9d6773ffd5efb

Observation 99b8ff4d-268d-4b90-b187-4090a64828b3 · outbound

This paper cites Sketch3D: Style- Consistent Guidance for Sketch-to-3D Generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review Sketch3D: Style- Consistent Guidance for Sketch-to-3D Generation

Reference 99

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source=pdf_text observed=2026-08-07T10:29:43.874159Z digest=sha256:c25a1dcb0b5c9ca520b3623049a4754e025e0495be5049cb6a8016e90f7ab8bf

Observation 3834e16c-05ea-4b51-912b-235087725b58 · outbound

This paper cites SpaceBlender: Creating Context- Rich Collaborative Spaces Through Generative 3D Scene Blending.

AI-powered Contextual 3D Environment Generation: A Systematic Review SpaceBlender: Creating Context- Rich Collaborative Spaces Through Generative 3D Scene Blending

Reference 100

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source=pdf_text observed=2026-08-07T10:29:43.879250Z digest=sha256:0f8268e643f8476127d51aac37d3a3fa4bcc4282204bbe9e6e6efb8d1aa50b14

Observation 98501fd6-f463-4206-9747-dbba734756f8 · outbound

This paper cites Knowl- edge Generation Pipeline using LLM for Building 3D Object Knowledge Base.

AI-powered Contextual 3D Environment Generation: A Systematic Review Knowl- edge Generation Pipeline using LLM for Building 3D Object Knowledge Base

Reference 101

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verified exact
raw_fallback, observed 2026-08-07T10:29:46.195192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.884471Z digest=sha256:183ee619bc155fecc7a2af03f67a0fecfb5f1962aca3e70c39b115132a0d6ce2

Observation 465dcd1e-c640-4726-ab18-8426162c76fe · outbound

This paper cites ControlStyle: Text-Driven Styl- ized Image Generation Using Diffusion Priors.

AI-powered Contextual 3D Environment Generation: A Systematic Review ControlStyle: Text-Driven Styl- ized Image Generation Using Diffusion Priors

Reference 102

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source=pdf_text observed=2026-08-07T10:29:43.889539Z digest=sha256:a630c8235493054d9b57b595b37ab7ae8f6c8bf93dc31ead60f60dac41676073

Observation 573ddb7c-7b6a-4fde-9047-a066bdc5515a · outbound

This paper cites ControlMat: A Controlled Generative Approach to Material Capture.

AI-powered Contextual 3D Environment Generation: A Systematic Review ControlMat: A Controlled Generative Approach to Material Capture

Reference 103

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source=pdf_text observed=2026-08-07T10:29:43.894461Z digest=sha256:bf461899c421d4e8959b510ec82ef4037ae469e1372d7de1256071bcda95236b

Observation db40e904-c449-49e3-8792-904325a84dc0 · outbound

This paper cites Diffusion Texture Painting.

AI-powered Contextual 3D Environment Generation: A Systematic Review Diffusion Texture Painting

Reference 104

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source=pdf_text observed=2026-08-07T10:29:43.899681Z digest=sha256:277b199d08a8d1e80c6da5b4300a8185d201e915336a2c00f088d3f69ecffe9f

Observation 63ac7ecf-9b17-48d4-b8a5-552872f09d42 · outbound

This paper cites MatFormer: a generative model for procedural materials.

AI-powered Contextual 3D Environment Generation: A Systematic Review MatFormer: a generative model for procedural materials

Reference 105

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source=pdf_text observed=2026-08-07T10:29:43.904681Z digest=sha256:f525bd0b7b956c9e391f36506f8b67344ec3db8faeb95796b01ef1900c5dfbef

Observation d068e563-c066-4678-9fed-fbb6bdfec7cf · outbound

This paper cites MaPa: Text-driven Photoreal- istic Material Painting for 3D Shapes.

AI-powered Contextual 3D Environment Generation: A Systematic Review MaPa: Text-driven Photoreal- istic Material Painting for 3D Shapes

Reference 106

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source=pdf_text observed=2026-08-07T10:29:43.909150Z digest=sha256:8147fcbd5bf090b8b3f6fad710ded4e5145090eab14e04d55f8cd7db99b07453

Observation e66b17fd-a5e6-4637-9b50-3aaa8966f311 · outbound

This paper cites PhotoMat: A Material Generator Learned from Single Flash Photos.

AI-powered Contextual 3D Environment Generation: A Systematic Review PhotoMat: A Material Generator Learned from Single Flash Photos

Reference 107

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source=pdf_text observed=2026-08-07T10:29:43.913553Z digest=sha256:510e5437ca7ed34715ca5da72f8eaa7ce6232f3346ac99ec0c11cb68e0b49ff9

Observation 796ebccb-8f4a-44c4-8df8-173163417271 · outbound

This paper cites Large Language and Text-to-3D Models for Engineer- ing Design Optimization.

AI-powered Contextual 3D Environment Generation: A Systematic Review Large Language and Text-to-3D Models for Engineer- ing Design Optimization

Reference 108

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source=pdf_text observed=2026-08-07T10:29:43.918065Z digest=sha256:0487b93f07b24065bf71c5659fb0a202027f3d9094cb672e6754b029cce8a457

Observation cd9b2d49-5724-4f23-9309-6e32aff584ad · outbound

This paper cites FloorGAN: Generative Net- work for Automated Floor Layout Generation.

AI-powered Contextual 3D Environment Generation: A Systematic Review FloorGAN: Generative Net- work for Automated Floor Layout Generation

Reference 109

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source=pdf_text observed=2026-08-07T10:29:43.922550Z digest=sha256:60f863182247b9d8a170d98cc23c034cd8ec787161645f64dcef012c8aea8ae4

Observation 610de5ab-8a0f-4e6d-8c93-91db75190406 · outbound

This paper cites Automated video editing based on learned styles using LSTM-GAN.

AI-powered Contextual 3D Environment Generation: A Systematic Review Automated video editing based on learned styles using LSTM-GAN

Reference 110

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source=pdf_text observed=2026-08-07T10:29:43.927746Z digest=sha256:ad3adf5f4d183f803e5d4a44b300f984f801b334f020ac7580b486a83e732f41

Observation 00f74d59-d106-4b49-abd1-a44dc4639d2b · outbound

This paper cites TexPainter: Generative Mesh Texturing with Multi-view Consistency.

AI-powered Contextual 3D Environment Generation: A Systematic Review TexPainter: Generative Mesh Texturing with Multi-view Consistency

Reference 111

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source=pdf_text observed=2026-08-07T10:29:43.933295Z digest=sha256:4eeab4329b57dd4a396c9a334f13d26aa484677740da408f78ab1075497763b9

Observation 013fe6fc-9676-4e17-a11e-f3da29301da7 · outbound

This paper cites ThemeStation: Generating Theme-Aware 3D Assets from Few Exemplars.

AI-powered Contextual 3D Environment Generation: A Systematic Review ThemeStation: Generating Theme-Aware 3D Assets from Few Exemplars

Reference 112

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source=pdf_text observed=2026-08-07T10:29:43.938916Z digest=sha256:b6ff554a32a5a264c24e942408c540eafad4830574c7d1d00871792704001124

Observation 4ff35044-537c-40a3-b0e9-5cd3c5ab7683 · outbound

This paper cites VDAM: V AE based domain adap- tation for cloud property retrieval from multi-satellite data.

AI-powered Contextual 3D Environment Generation: A Systematic Review VDAM: V AE based domain adap- tation for cloud property retrieval from multi-satellite data

Reference 113

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.944317Z digest=sha256:9d5a8a9a3a8f613e940b77df5ffc5f20b96a272b1c73232094ec126af55f98eb

Observation b946eb8b-3637-4b1e-8786-ce65c89eba2d · outbound

This paper cites Cascade Variational Auto-Encoder for Hierarchical Disentanglement.

AI-powered Contextual 3D Environment Generation: A Systematic Review Cascade Variational Auto-Encoder for Hierarchical Disentanglement

Reference 114

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source=pdf_text observed=2026-08-07T10:29:43.949622Z digest=sha256:32225984ba52c805f93aab3307ef0581a707ed5d6244f36b3a108cf38b694fb8

Observation 53f8e540-35ad-4acd-9dd2-106eab4d4eca · outbound

This paper cites Automated Testing of Graphics Units by Deep-Learning Detection of Vi- sual Anomalies.

AI-powered Contextual 3D Environment Generation: A Systematic Review Automated Testing of Graphics Units by Deep-Learning Detection of Vi- sual Anomalies

Reference 115

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source=pdf_text observed=2026-08-07T10:29:43.954828Z digest=sha256:f89202a0873a1bdec5bd97e275e8a3c33918ec8c8c2b202341598b769d61a23f

Observation af395e08-654b-4d61-8e66-e38c54440ba9 · outbound

This paper cites RealFill: Reference-Driven Gen- eration for Authentic Image Completion.

AI-powered Contextual 3D Environment Generation: A Systematic Review RealFill: Reference-Driven Gen- eration for Authentic Image Completion

Reference 116

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source=pdf_text observed=2026-08-07T10:29:43.959432Z digest=sha256:b0ce5c5e121ea5b246f61ef6154d6c47d35391017fa22a8e59787df972a7a0aa

Observation b8a401df-4ebc-443c-9cd8-930b99b801f4 · outbound

This paper cites A Survey on Deep Generative 3D-aware Image Synthesis.

AI-powered Contextual 3D Environment Generation: A Systematic Review A Survey on Deep Generative 3D-aware Image Synthesis

Reference 117

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.964577Z digest=sha256:fb872d1ab2633e9c89cef76777345130dfc3e6f25af5beb175a3b36b28cd91dd

Observation c674e73c-b5fb-49d3-941a-c6739e8912c1 · outbound

This paper cites Image Generation Model Applying PCA on Latent Space.

AI-powered Contextual 3D Environment Generation: A Systematic Review Image Generation Model Applying PCA on Latent Space

Reference 118

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metadata mismatch
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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.970571Z digest=sha256:42ee574b795597d1a09d1df97c8d2ae26c5eb31317f45c4849f3ffc194841f7c

Observation 30c31e86-ffa1-47a0-9134-b760c46f1632 · outbound

This paper cites Broomrocket: Open Source Text-to-3D Algorithm for 3D Object Placement.

AI-powered Contextual 3D Environment Generation: A Systematic Review Broomrocket: Open Source Text-to-3D Algorithm for 3D Object Placement

Reference 119

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T10:29:43.976024Z digest=sha256:ecafe148209aa143be6150c0f9d630df20875ac9604dce7e06eeb6767b018dd6

Observation db2fea98-57c4-4dad-9bfd-520a1d26d148 · outbound

This paper cites Image based and Point Cloud based Methods for 3D View Reconstruction in Real- time Environment.

AI-powered Contextual 3D Environment Generation: A Systematic Review Image based and Point Cloud based Methods for 3D View Reconstruction in Real- time Environment

Reference 120

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source=pdf_text observed=2026-08-07T10:29:43.981667Z digest=sha256:3d050811d72e9cc94edf28c1a505b943c7fb2aef1f65b16621070044bc9f29fd

Observation 675a851a-5572-4488-96ee-168c4bea31d6 · outbound

This paper cites GenQuery: Supporting Expressive Visual Search with Generative Models.

AI-powered Contextual 3D Environment Generation: A Systematic Review GenQuery: Supporting Expressive Visual Search with Generative Models

Reference 121

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source=pdf_text observed=2026-08-07T10:29:43.987275Z digest=sha256:c9ef4ac8c414edef334f39b0b4d255579ea9bc6c42808d201bd3981b61210308

Observation c17a7cff-b284-4a42-9afa-f26a9c338a14 · outbound

This paper cites Prompt- Paint: Steering Text-to-Image Generation Through Paint Medium-like Interactions.

AI-powered Contextual 3D Environment Generation: A Systematic Review Prompt- Paint: Steering Text-to-Image Generation Through Paint Medium-like Interactions

Reference 122

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source=pdf_text observed=2026-08-07T10:29:43.992088Z digest=sha256:f87c7193e6d339e70ca33dcb56dad8991e43340d78363899cf588ba7ce5a4144

Pith citing papers

No inbound Pith citation observations are available.