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Paper Citation Record · LEDGER

Semantic-Guided Progressive Object Removal with Gaussian Splatting

As of 7 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2607.04144.

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

pith.paper-citation-record.v1
2607.04144 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T21:22:53.477128Z

measured 49 of 49 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

49 of 49 outbound references displayed

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  • unresolved49
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  • malformed identifier0
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External citation measurements

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Outbound references

Observation b667e0be-4938-49df-b601-2a738897ad3a · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Nerf: Representing scenes as neural radiance fields for view synthesis,

Reference 1

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:2878fa3b371294d84723ea53fd0046daccffccc82ec8d1f37bd388577adf1021

Observation 68f5a81e-bd00-4a1c-b7b1-82144f328d10 · outbound

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

Semantic-Guided Progressive Object Removal with Gaussian Splatting 3d gaussian splatting for real-time radiance field rendering

Reference 2

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:e015f6854c144695b021c71267938183bb977152d6b06e0444a3ef8ab0377609

Observation cba4d530-8cb5-43ce-97da-65d5a3418c19 · outbound

This paper cites LIVE-GS: LLM Powers Interactive VR Experience with Physics-Aware Gaussian Splatting.

Semantic-Guided Progressive Object Removal with Gaussian Splatting LIVE-GS: LLM Powers Interactive VR Experience with Physics-Aware Gaussian Splatting

Reference 3

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:2178f6596c4bdfd7e78aae6d33a452166636bf5c09d439253a033dfe2bd3ecdc

Observation 199d10ae-aff7-40a6-bf01-b0164ffcc6e5 · outbound

This paper cites Mace: Mixture-of-experts accelerated coordinate encoding for large-scale scene localization and rendering,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Mace: Mixture-of-experts accelerated coordinate encoding for large-scale scene localization and rendering,

Reference 4

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:c2276c8749085b74d050f4ee0faaedd363cdccbbb433145096699177a23221ec

Observation 0f4468ff-9204-418e-92f5-2a3e2f9ff799 · outbound

This paper cites MIND-V: Hierarchical World Model for Long-Horizon Robotic Manipulation with RL-based Physical Alignment.

Semantic-Guided Progressive Object Removal with Gaussian Splatting MIND-V: Hierarchical World Model for Long-Horizon Robotic Manipulation with RL-based Physical Alignment

Reference 5

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:457ccf6d91e56faffe6c6445494379f7428dd7748ee6e017ce4084dd660f2b18

Observation a0d5ee92-b010-450c-8c1e-1b61b5373541 · outbound

This paper cites Drivinggaussian: Composite gaussian splatting for surrounding dy- namic autonomous driving scenes,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Drivinggaussian: Composite gaussian splatting for surrounding dy- namic autonomous driving scenes,

Reference 6

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:fa4768dd96f182f4efd353febb324fafdc093429837a2ddbdfaa0b5ac136daef

Observation db0212dd-bf25-4817-872e-7b0074230ff4 · outbound

This paper cites SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fields.

Semantic-Guided Progressive Object Removal with Gaussian Splatting SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fields

Reference 7

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:2817fafbe04b698c60fd99d4ecfecfddb86b6c01cdfd584e2fead26294bdd286

Observation 364973ab-e9a8-43a9-9bf1-4a56fcbf41e1 · outbound

This paper cites Gaussianeditor: Swift and controllable 3d editing with gaussian splatting,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Gaussianeditor: Swift and controllable 3d editing with gaussian splatting,

Reference 8

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:b46f570c2cb66d9b44df7149767b5f982403ec074d623e8138d4d8d793984301

Observation b8633e50-33f4-440a-b32d-47bc6031757b · outbound

This paper cites Nerf-mir: Toward high-quality restoration of masked images with neural radiance fields,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Nerf-mir: Toward high-quality restoration of masked images with neural radiance fields,

Reference 9

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:f8441ea69d433511d3508394aa3af7811387e6bace7643345fc7a5461d4e75be

Observation 211aa3cd-bd38-4c66-8387-00cf550244e1 · outbound

This paper cites Mvip-nerf: Multi-view 3d inpainting on nerf scenes via diffusion prior,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Mvip-nerf: Multi-view 3d inpainting on nerf scenes via diffusion prior,

Reference 10

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:bbf49f3fd8d285c8229745a944e7230758ed730d13c916102bc47454e80c4d69

Observation 446cc0ed-b3e8-4049-9502-0666eb32f148 · outbound

This paper cites InFusion: Inpainting 3D Gaussians via Learning Depth Completion from Diffusion Prior.

Semantic-Guided Progressive Object Removal with Gaussian Splatting InFusion: Inpainting 3D Gaussians via Learning Depth Completion from Diffusion Prior

Reference 11

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:e627bd5bd0a694f19a909f896f1d32549f2eec450fc91fe21b34b530e2c0db52

Observation bc6469f4-cd38-4e89-8901-6cf61a87c44f · outbound

This paper cites Generative object insertion in gaussian splatting with a multi-view diffusion model,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Generative object insertion in gaussian splatting with a multi-view diffusion model,

Reference 12

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:0964ada2258ed3914188f3444827ab8b8665edecb06da740f9ed34e5a6a4a58a

Observation 386399d6-3e79-4b99-bc66-6f3f62ed8d71 · outbound

This paper cites DreamFusion: Text-to-3D using 2D Diffusion.

Semantic-Guided Progressive Object Removal with Gaussian Splatting DreamFusion: Text-to-3D using 2D Diffusion

Reference 13

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:2cd2a55cacd9a49387432bfe741d8367ab68d4f83cfb26b0f37ef202046416d0

Observation 3a6879ad-c451-40bd-a745-97bc6289e20d · outbound

This paper cites Seeing the unseen: A frequency prompt guided transformer for image restoration,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Seeing the unseen: A frequency prompt guided transformer for image restoration,

Reference 14

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:91e482ab58b82d05e39ce58c5897031f90d9b88599df8ff9409f1b43effd698a

Observation 57a7ad37-b1df-4706-ae1f-47951727be8c · outbound

This paper cites Devil is in the uniformity: Exploring diverse learners within transformer for image restoration,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Devil is in the uniformity: Exploring diverse learners within transformer for image restoration,

Reference 15

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:d3e6dec114053e2a918dcb62cdde81ea5819cf5e8b689d7aac0b89b97b0681d8

Observation b692d79a-ba3a-4b52-9f47-afe00715c9ce · outbound

This paper cites Denoising diffusion probabilistic models,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Denoising diffusion probabilistic models,

Reference 16

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:bbe17da954d6e921f6b86dfbf101aa8bdd6d6e7fb155f07c108d23dc2c98c062

Observation b1e8f68f-45f7-45a3-b09a-1623b27cbb82 · outbound

This paper cites Iddr-ngp: Incorporating detectors for distractors removal with instant neural radiance field,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Iddr-ngp: Incorporating detectors for distractors removal with instant neural radiance field,

Reference 17

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:d01cd78c35c977dbff1f214433ce40e0514e13efd96df6c23c408856b9f3008e

Observation 329981fc-889b-468b-b12e-558ba055216b · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting High-resolution image synthesis with latent diffusion models,

Reference 18

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:1a0850acd14b42cee7a91f518329e920bf3f013d5c74878f629a6607a354a41b

Observation 05a2bd8a-e0f0-4bad-8ce3-a05f79e6358d · outbound

This paper cites Learning an adaptive sparse transformer for efficient image restoration,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Learning an adaptive sparse transformer for efficient image restoration,

Reference 19

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:d5368db6ca1bf786c4a33ffd0aab1338d97656bd3f480f6526e07e194d054d7c

Observation e95efe6d-cf65-40a1-804b-2a6f85f33211 · outbound

This paper cites Text-driven image editing via learnable regions,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Text-driven image editing via learnable regions,

Reference 20

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:0d2e2d16609ecf702e5d1d198fee198d52be940dcab67cf206ebc38c0b229ba0

Observation a928abb1-5687-49a7-93f7-6eb8b7302aa0 · outbound

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

Semantic-Guided Progressive Object Removal with Gaussian Splatting Adding conditional control to text-to-image diffusion models,

Reference 21

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:14618b6068f0d811c700ffe0bf1275d3d6817021c055b51d9c89f1069913586f

Observation b4b0391a-8a66-4c96-a8c8-0eae80b99afb · outbound

This paper cites Spatext: Spatio-textual repre- sentation for controllable image generation,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Spatext: Spatio-textual repre- sentation for controllable image generation,

Reference 22

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:c4f0c8deb2053e3153d772d0d9c87d387511be23f0d539f03ec4c6b7f584be86

Observation 2ac90fb6-2f68-4e4e-98fd-48bcfd731fd9 · outbound

This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject- driven generation,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Dreambooth: Fine tuning text-to-image diffusion models for subject- driven generation,

Reference 23

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:f04d9cc62d7a788748a6a007681fdce2aabbefed79b9255099e8cd2a81a6c0c3

Observation 3a964559-5ef1-4dc4-aeec-ec227cb8c874 · outbound

This paper cites An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.

Semantic-Guided Progressive Object Removal with Gaussian Splatting An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

Reference 24

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:80fabd24a9d0af40743e7f349f49ac720db6f94bf62ffc3792b54bc91521393c

Observation 8eecd53c-1ee6-496d-bdef-c184d814f977 · outbound

This paper cites SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations.

Semantic-Guided Progressive Object Removal with Gaussian Splatting SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations

Reference 25

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:898efd85b320ee3d3fdc286b48560f0e338a6bcf62cf41b038724a087e5975c0

Observation 6e19bd6d-8aa8-487a-a06b-fea7039da75a · outbound

This paper cites Diffusion models beat gans on image synthesis,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Diffusion models beat gans on image synthesis,

Reference 26

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:0854f29706214aa0d7f9e9c889455ef63781257f529f82d222b77101a9cb14e7

Observation f7876b7e-8a3d-4669-aadc-c9f1c29e8157 · outbound

This paper cites Denoising Diffusion Implicit Models.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Denoising Diffusion Implicit Models

Reference 27

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:9f9db07a21f15584c86f958e603f862f1fefe6032fe888db75072dba2f1b6036

Observation c90d2274-18a9-442a-8acb-050965fb7182 · outbound

This paper cites Deepsdf: Learning continuous signed distance functions for shape representation,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Deepsdf: Learning continuous signed distance functions for shape representation,

Reference 28

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:e148eb80f3b07c651f2fcd7494d89c2415427d55df96718ccc278080ad84c72f

Observation 76606e1b-9c8a-4074-9534-5b49f5742bac · outbound

This paper cites Shape inpainting using 3d generative adversarial network and recurrent convolutional networks,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Shape inpainting using 3d generative adversarial network and recurrent convolutional networks,

Reference 29

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:3cf1a95e9d217d5562789c7fbdbd72435e909aadf423f91f19767523c8a08b4b

Observation 7aba8f61-ca1d-474a-be0b-03193f92484c · outbound

This paper cites Textde- former: Geometry manipulation using text guidance,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Textde- former: Geometry manipulation using text guidance,

Reference 30

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:b8f58729d72616778c1e5fa695506b60399c35f21672b5c129255438b8ac5cc7

Observation 833060e6-608b-472e-988c-1a536203612c · outbound

This paper cites Clip-nerf: Text-and- image driven manipulation of neural radiance fields,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Clip-nerf: Text-and- image driven manipulation of neural radiance fields,

Reference 31

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Observation 1ef0c9db-09cb-4a36-83fb-8d0bc2337942 · outbound

This paper cites Dreameditor: Text- driven 3d scene editing with neural fields,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Dreameditor: Text- driven 3d scene editing with neural fields,

Reference 32

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:2efd184328d7fd7dea3f4f31aa5c333521e4c96f70a25b9820357edfc0737341

Observation 78b08c4d-3c8a-40d8-b9e8-a84cd82b2b43 · outbound

This paper cites Hi-nerf: Hybridizing 2d inpainting with neural radiance fields for 3d scene inpainting,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Hi-nerf: Hybridizing 2d inpainting with neural radiance fields for 3d scene inpainting,

Reference 33

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:8bd107de306c367025eddbff156c907e6449b5b33e31b14b8f3bba3dd44c4a06

Observation e99282cc-0902-457a-9c81-f74e524413d7 · outbound

This paper cites Text2mesh: Text-driven neural stylization for meshes,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Text2mesh: Text-driven neural stylization for meshes,

Reference 34

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:1df875224f274978bc977eb83f74ef0a95ca9a97b3fbf8b53580a6793ab06369

Observation bb306415-d3c2-4f65-9052-82959417011e · outbound

This paper cites Nerfiller: Completing scenes via generative 3d inpainting,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Nerfiller: Completing scenes via generative 3d inpainting,

Reference 35

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:9eb071badb50438e2e48ab34d85d687715c1a2e0cc2fc08191ef1eab841bfe44

Observation d557de7e-5f29-4d70-9f3c-c7c311e0dd04 · outbound

This paper cites Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects

Reference 36

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Observation cf067f96-6c27-41ed-930d-98aa28def63c · outbound

This paper cites Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Prompts.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Progressive3D: Progressively Local Editing for Text-to-3D Content Creation with Complex Semantic Prompts

Reference 37

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:2a61df9674cfa4a8ff724052de9f510376fbef464f1f0dbde3999ad7e5a98aac

Observation cea278f9-23b7-4594-bf5a-2844262f6f6e · outbound

This paper cites Gaussian grouping: Segment and edit anything in 3d scenes,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Gaussian grouping: Segment and edit anything in 3d scenes,

Reference 38

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:748d6ce0ef8b5dcc4aef1117b4dc02a3d9a184d613150b6108da92b43616313c

Observation 5bfe80cd-2b2c-4fdc-a865-4f5e876e8fad · outbound

This paper cites Learning 3d geometry and feature consistent gaussian splatting for object removal,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Learning 3d geometry and feature consistent gaussian splatting for object removal,

Reference 39

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:e691c7b4cb639a2693278be5490ab228bbb3b07927522d07f96f5db329fa4b00

Observation 79225f57-8835-421c-ac81-db39dbf45264 · outbound

This paper cites MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing.

Semantic-Guided Progressive Object Removal with Gaussian Splatting MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing

Reference 40

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:408c5b8b8fdcec035c0bcc81678ff4f3aca9c6b9ac76addba44bb0503efe6c34

Observation 595bfa71-8952-48b5-aa47-4a5c48eedf70 · outbound

This paper cites Ewa volume splatting,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Ewa volume splatting,

Reference 41

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:b04c6b8781106ff7a71a0b44a9e287fbf64b2b071cb99859d89b611430e62481

Observation 20f07863-a757-4981-b12e-6eb20a3730a1 · outbound

This paper cites Optical models for direct volume rendering,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Optical models for direct volume rendering,

Reference 42

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:4ce295995fae3f2582743e6ca14ae7abf3a2ccefe803786bca60229a20773b18

Observation 005ddb4f-6c4c-4fbf-b28b-b127b542c56b · outbound

This paper cites Resolution-robust large mask inpainting with fourier convolutions,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Resolution-robust large mask inpainting with fourier convolutions,

Reference 43

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:cacbe991f03bab8822e59916ceaf67810fb1eec66f4676c2d0c4e1416941dae3

Observation 5f728d72-3498-42e0-af5f-2b0ee3495530 · outbound

This paper cites Structure-from-motion revisited,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Structure-from-motion revisited,

Reference 44

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:e916738654e2dc759aa36aca76a6faf583a28abbd75f72139d2d8223c555324c

Observation d8d03820-2c4d-45c9-9dc4-466b7b0ba3cc · outbound

This paper cites Design of an image edge detection filter using the sobel operator,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Design of an image edge detection filter using the sobel operator,

Reference 45

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:d6d31d2cd4c5fe0a9c8d376e6f09416bc2abccf7880695e457e9b0dd407b50df

Observation dec4b7ee-bf03-41e1-97da-8ba633af45cd · outbound

This paper cites Image quality assessment: from error visibility to structural similarity,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Image quality assessment: from error visibility to structural similarity,

Reference 46

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:7e43493c4a87e3d9ed500c95c8b47b617f0eba2ff6115a6bd9765b9843eabef0

Observation 22a9ab71-d7e6-4fc3-86b8-f3c3891cff93 · outbound

This paper cites Local light field fusion: Practical view synthesis with prescriptive sampling guidelines,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Local light field fusion: Practical view synthesis with prescriptive sampling guidelines,

Reference 47

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:2de0674bd01ba346e841af9d5e6eb5cac3174261b096de6053ad1cbe1a457d2c

Observation e661ce51-051a-445d-a490-94a9b72379ea · outbound

This paper cites Mip-nerf 360: Unbounded anti-aliased neural radiance fields,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting Mip-nerf 360: Unbounded anti-aliased neural radiance fields,

Reference 48

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:aa3835c6e4acf26b78b80f29be6888a3ba606a8f7ff432232ddad16fc47fbb6d

Observation 99babf3c-943f-47d9-b40a-ccbaae9cea5b · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric,.

Semantic-Guided Progressive Object Removal with Gaussian Splatting The unreasonable effectiveness of deep features as a perceptual metric,

Reference 49

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source=pdf_text observed=2026-07-11T21:22:53.477128Z digest=sha256:bda0db85df8f5998c4c29b636dce8514d72ddb3a52dd7a27a2ee86fae0c0236e

Pith citing papers

No inbound Pith citation observations are available.