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Paper Citation Record · LEDGER

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction

As of 19 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 1 inbound Pith citation observation for arXiv:2507.21960.

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

pith.paper-citation-record.v1
2507.21960 v1

Coverage vector

measured 78 of 78 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:17:22.380837Z

measured 79 of 79 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T18:25:15.494462Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T00:35:52.829379Z

Reference resolution

78 of 78 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 72c90086-6267-4537-b1eb-5dd90969d49c · outbound

This paper cites Elite360d: Towards efficient 360 depth estimation via semantic-and distance-aware bi- projection fusion.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Elite360d: Towards efficient 360 depth estimation via semantic-and distance-aware bi- projection fusion

Reference 1

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 88852037-94ec-43fc-9e9c-1604bd6c0656 · outbound

This paper cites Hrdfuse: Monocular 360deg depth estimation by collaboratively learning holistic-with-regional depth distri- butions.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Hrdfuse: Monocular 360deg depth estimation by collaboratively learning holistic-with-regional depth distri- butions

Reference 2

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2355d54c-5c91-428c-9bfe-cfaf82ff2a96 · outbound

This paper cites Virtual reality and 360 panorama technology: a media comparison to study changes in sense of presence, anxiety, and positive emotions.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Virtual reality and 360 panorama technology: a media comparison to study changes in sense of presence, anxiety, and positive emotions

Reference 3

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5943ffa7-e75b-430d-8b01-fa2315b38162 · outbound

This paper cites pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction pixelsplat: 3d gaussian splats from image pairs for scalable generalizable 3d reconstruction

Reference 4

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation db71a7e4-7c32-4803-ad4e-81e06a4beefb · outbound

This paper cites VI3DRM:Towards meticulous 3D Reconstruction from Sparse Views via Photo-Realistic Novel View Synthesis.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction VI3DRM:Towards meticulous 3D Reconstruction from Sparse Views via Photo-Realistic Novel View Synthesis

Reference 5

Resolution
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local_arxiv, observed 2026-08-06T12:17:22.517788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e7d9b26c-b488-4bbb-959d-63686fd1a680 · outbound

This paper cites ZeroGS: Training 3D Gaussian Splatting from Unposed Images.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction ZeroGS: Training 3D Gaussian Splatting from Unposed Images

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:17:22.502573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation ce58159e-0ab6-45b2-9db9-7b38e823135d · outbound

This paper cites Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Mvsplat: Efficient 3d gaussian splatting from sparse multi-view images

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 1a942e16-4f42-424c-90e0-c5e937d3e885 · outbound

This paper cites Panogrf: generalizable spherical radiance fields for wide-baseline panoramas.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Panogrf: generalizable spherical radiance fields for wide-baseline panoramas

Reference 8

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 313d6783-f725-4fd9-8c12-a17d5290068b · outbound

This paper cites PreF3R: Pose-Free Feed-Forward 3D Gaussian Splatting from Variable-length Image Sequence.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction PreF3R: Pose-Free Feed-Forward 3D Gaussian Splatting from Variable-length Image Sequence

Reference 9

Resolution
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Source-reported events for the cited work

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Observation 7f2d32d3-26fa-41fe-adf3-8e06dd6d314d · outbound

This paper cites Splatter-360: Generalizable 360 gaussian splatting for wide- baseline panoramic images.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Splatter-360: Generalizable 360 gaussian splatting for wide- baseline panoramic images

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 47de64fe-a815-4dc5-ba7b-761d425a8606 · outbound

This paper cites Spherenet: Learning spherical representations for detection and classification in omnidirectional images.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Spherenet: Learning spherical representations for detection and classification in omnidirectional images

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4b5ba402-184b-48c1-a5a9-16d923b175e5 · outbound

This paper cites Eliminating the blind spot: Adapting 3d object detection and monocular depth estimation to 360 panoramic imagery.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Eliminating the blind spot: Adapting 3d object detection and monocular depth estimation to 360 panoramic imagery

Reference 12

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2763b3bc-8402-4694-a0b6-dba80099b8e9 · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction An image is worth 16x16 words: Trans- formers for image recognition at scale

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:23.094535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 10f9d6b6-9b2a-407d-8dfe-80c11476b835 · outbound

This paper cites Pano popups: In- door 3d reconstruction with a plane-aware network.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Pano popups: In- door 3d reconstruction with a plane-aware network

Reference 14

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 5a68ab0b-c86f-454c-86aa-a2908d0371b5 · outbound

This paper cites Tangent images for mitigating spherical distortion.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Tangent images for mitigating spherical distortion

Reference 15

Resolution
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Source-reported events for the cited work

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Observation e5f2b652-2d9b-4280-b75e-70a8b759afb1 · outbound

This paper cites Desktop-based safety training using 360-degree panorama and static virtual reality techniques: A comparative exper- imental study.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Desktop-based safety training using 360-degree panorama and static virtual reality techniques: A comparative exper- imental study

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 95e0de2b-b6d8-408c-ae18-eeebd0c788c1 · outbound

This paper cites InstantSplat: Sparse-view Gaussian Splatting in Seconds.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction InstantSplat: Sparse-view Gaussian Splatting in Seconds

Reference 17

Resolution
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Source-reported events for the cited work

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Observation a797cb6f-0413-4eb0-929d-592533690c5b · outbound

This paper cites Large spatial model: End-to-end unposed images to semantic 3d.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Large spatial model: End-to-end unposed images to semantic 3d

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation ca0b95d8-2e95-4a94-b12c-c5a61be0edb6 · outbound

This paper cites Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Communications of the ACM, 24(6):381–395, 1981.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography.Communications of the ACM, 24(6):381–395, 1981

Reference 19

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 48f41d97-d0fb-46bb-a437-2fa36b8e7b3c · outbound

This paper cites Forward flow for novel view synthesis of dynamic scenes.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Forward flow for novel view synthesis of dynamic scenes

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 498110ea-e23a-48fa-97f2-59439b07e5c1 · outbound

This paper cites Somsi: Spherical novel view synthesis with soft occlusion multi-sphere images.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Somsi: Spherical novel view synthesis with soft occlusion multi-sphere images

Reference 21

Resolution
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Source-reported events for the cited work

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Observation 21debe34-d80a-4270-94c1-277c7d027a2d · outbound

This paper cites In defense of the eight-point algorithm.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction In defense of the eight-point algorithm

Reference 22

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Source-reported events for the cited work

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Observation fe0ecb9a-e880-4a4f-9033-49faac9fc7e8 · outbound

This paper cites Rotary position embedding for vision transformer.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Rotary position embedding for vision transformer

Reference 23

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0ffa1fa9-c592-4e75-9f88-d8977a279e69 · outbound

This paper cites 2d gaussian splatting for geometrically ac- curate radiance fields.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction 2d gaussian splatting for geometrically ac- curate radiance fields

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e4f080dc-5a2e-4a46-b880-e2d298e45b3a · outbound

This paper cites Unifuse: Unidirectional fusion for 360 panorama depth estimation.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Unifuse: Unidirectional fusion for 360 panorama depth estimation

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.967794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9c5a03a6-e14d-4f7f-90ad-7a6f91c77baf · outbound

This paper cites Stereo4d: Learning how 9 things move in 3d from internet stereo videos.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Stereo4d: Learning how 9 things move in 3d from internet stereo videos

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation bb57aeaa-0a90-4b96-ac80-996f00382d89 · outbound

This paper cites Selfsplat: Pose-free and 3d prior-free generalizable 3d gaussian splatting.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Selfsplat: Pose-free and 3d prior-free generalizable 3d gaussian splatting

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.947088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 37484b48-842a-4baf-bbc6-43a4a4f856ac · outbound

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

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction 3d gaussian splatting for real-time radiance field rendering

Reference 28

Resolution
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Source-reported events for the cited work

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Observation 0c9118f2-6535-4f4a-829b-a78e5f2e1f72 · outbound

This paper cites xformers: A modular and hackable trans- former modelling library.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction xformers: A modular and hackable trans- former modelling library

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8bc6c4b4-0819-475f-972f-6f110d50fc91 · outbound

This paper cites Slam with panoramic vision.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Slam with panoramic vision

Reference 30

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 86a0404c-02b3-41b4-9899-e6c46d164629 · outbound

This paper cites Ep n p: An accurate o (n) solution to the p n p problem.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Ep n p: An accurate o (n) solution to the p n p problem

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.912453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 23cfa5e2-ecba-46e1-8787-0e8b81dcf67c · outbound

This paper cites Ground- ing image matching in 3d with mast3r.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Ground- ing image matching in 3d with mast3r

Reference 32

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.226082Z digest=sha256:34de14ea038e24b7841d1d3f82bd46a50c7624777089a994e8b3b4fe853a71db

Observation 60df0833-000b-485a-9ba3-c56506844e3e · outbound

This paper cites ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T12:17:22.229251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:22.229251Z digest=sha256:5bb727a6b3d7082c4f5c33f0afa7a1d748ac5b72d4f62153504fd214c7aba5d8

Observation 1d2012a8-896d-4019-9a9f-c53f292c5449 · outbound

This paper cites Augmented reality: a novel approach for navigating in panorama-based virtual environments (pbve).

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Augmented reality: a novel approach for navigating in panorama-based virtual environments (pbve)

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.890644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.233029Z digest=sha256:e22fad3f0797b000b82791175c6b939f8e856faa749d3532ab3bc14783998986

Observation 51026a94-4da7-4709-aefb-140393362200 · outbound

This paper cites Neural rays for occlusion-aware image-based ren- dering.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Neural rays for occlusion-aware image-based ren- dering

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.880714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.237024Z digest=sha256:0d5a738d8863a8b1b43ff3f25921955395a53cf8f91ee1f17f450eeb9f32aea7

Observation 90dd5e9c-0e66-4dad-8f2a-10ce74728608 · outbound

This paper cites Slam3r: Real- time dense scene reconstruction from monocular rgb videos.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Slam3r: Real- time dense scene reconstruction from monocular rgb videos

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.870331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.240474Z digest=sha256:693dc8a20c6e107b41d7cd8d208515f1dd2fb353d13ccfd4f04a0dd99d70267e

Observation b0dcb0ce-383b-4b09-b921-b996ca4e57ac · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Swin transformer: Hierarchical vision transformer using shifted windows

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.860288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.243777Z digest=sha256:87dd1a807f2e751841459b5cc777f1cf85694640a84961e48e01c78dff2d8fbc

Observation 5e9f02a7-2f95-489e-b374-e1efcb8649eb · outbound

This paper cites Decoupled Weight Decay Regularization.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Decoupled Weight Decay Regularization

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T12:17:22.247119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:22.247119Z digest=sha256:02b8f0f57875746e1f92cb4bded6bae267c04dc4a8936be50aadb23becbb8de8

Observation b97128b8-da51-4aae-9c84-cb7f162e2ceb · outbound

This paper cites Distinctive image features from scale- invariant keypoints.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Distinctive image features from scale- invariant keypoints

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.849732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.250564Z digest=sha256:fd277292bc273bff9f0563484b9365f8e4c6b3575e795960637972e1a23ceefe

Observation 8bd51354-11e7-4c63-b5c9-f3b4c89c1393 · outbound

This paper cites Align3r: Aligned monocular depth estima- tion for dynamic videos.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Align3r: Aligned monocular depth estima- tion for dynamic videos

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.839798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.253746Z digest=sha256:0074f98fca3596bf29431c0f49965d4e66a5bac84f7f1c59104b65ce47bcd772

Observation 2b5af00c-d28a-4510-8100-7467dd7ede0b · outbound

This paper cites 3d geometry-aware deformable gaussian splatting for dynamic view synthesis.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction 3d geometry-aware deformable gaussian splatting for dynamic view synthesis

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.830029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.257653Z digest=sha256:9fd938da2bf8b9fcee2a7dc9f89064fea8536166aeb15acf5052d1015a4034fd

Observation 86ac9c12-0e35-40b9-92dc-2e2e61a56fc3 · outbound

This paper cites Fit: Flexible vision trans- former for diffusion model.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Fit: Flexible vision trans- former for diffusion model

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.818001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.261199Z digest=sha256:4e42847a855214f464fe20cf3cd5cc204fdb992184cb1d66a4ad30833cf44090

Observation 2da80b1c-1d79-4af8-82b8-971e04d9ebe9 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view syn- thesis.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.807028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.264516Z digest=sha256:37024e5ee4f2cba67399cb376130924e6c597be24665d1f7968d754551ff7baf

Observation dc0154d8-8807-4205-ba31-34cb2a99d302 · outbound

This paper cites Epipolar-free 3d gaussian splatting for generalizable novel view synthesis.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Epipolar-free 3d gaussian splatting for generalizable novel view synthesis

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.795592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.268747Z digest=sha256:4b3b42a9595185f890063597287874cdef60d1135878dbb11e5452dd2f7cf9c2

Observation 530d6d89-2bfc-4418-94e2-98e25a08c123 · outbound

This paper cites High-resolution depth estimation for 360deg panoramas through perspective and panoramic depth images registration.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction High-resolution depth estimation for 360deg panoramas through perspective and panoramic depth images registration

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.783420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.272103Z digest=sha256:faecb4f4ced817aa61736ddce96cdb064491d122133ff4c827b2f2200acad722

Observation 7dc95146-5054-46d3-a824-b38b0afe7558 · outbound

This paper cites Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T12:17:22.275400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:22.275400Z digest=sha256:1bb3acaaad980e3018a238e1ebd3da080f690f9d508c9c86147229ab85fe6144

Observation e17ffe53-e363-485b-a365-5bdc1eaec268 · outbound

This paper cites Vi- sion transformers for dense prediction.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Vi- sion transformers for dense prediction

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.772985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.278895Z digest=sha256:3cdf67438cc103fc9924b03b6517d73380b2431639c6600c4001776ca8f8334a

Observation 14782010-ae63-4491-b1c8-74c1e3f1a303 · outbound

This paper cites 360monodepth: High-resolution 360deg monocular depth estimation.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction 360monodepth: High-resolution 360deg monocular depth estimation

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.763196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.282256Z digest=sha256:f0cfd6ba8aecbbbde43dd8eb79669334e6c7be2c279e996f0dcd97885c0764fe

Observation 8f5f8ab2-2507-49d8-b7b5-928a7172df46 · outbound

This paper cites Habitat: A plat- form for embodied ai research.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Habitat: A plat- form for embodied ai research

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.753378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.285376Z digest=sha256:7f6be398f2f9e8c5a4d8afead22edac44f8ca23e39b1008ff48636779880acaf

Observation d4f90a02-4a1b-4c03-bec8-132c802ef171 · outbound

This paper cites Panoformer: Panorama transformer for indoor 360 depth estimation.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Panoformer: Panorama transformer for indoor 360 depth estimation

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.743660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.289816Z digest=sha256:07d031655bdc788930419d36ee9d3e026bb4eb4da7fa734a1c2b1b494209ca05

Observation 23c9bb5d-5a5a-4baf-a3a7-9e830f336b85 · outbound

This paper cites Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Splatt3R: Zero-shot Gaussian Splatting from Uncalibrated Image Pairs

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T12:17:22.293175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:22.293175Z digest=sha256:ff66bc95163e58cc00c05eb0c431f662a98078d616be481e0bd0f8ccf6f9d6c1

Observation 544fca2d-5886-40b1-8b71-722bcf55ce23 · outbound

This paper cites The Replica Dataset: A Digital Replica of Indoor Spaces.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction The Replica Dataset: A Digital Replica of Indoor Spaces

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T12:17:22.297496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:22.297496Z digest=sha256:05152a174e249653b0d3e34d6a554285d177a706ba6fb9761037cf8ebaa37c5d

Observation 791c1fa9-3f12-45ec-9d2c-1be9ca87dec9 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Roformer: Enhanced transformer with rotary position embedding

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T12:17:22.301243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:22.301243Z digest=sha256:d25dd6b55f72a9bc28a94189c7d9dd72d24aefc829d90d8d501155826cddb0d2

Observation 4a4a5751-46fd-445d-ac55-09d25f6b86c9 · outbound

This paper cites Hohonet: 360 indoor holistic understanding with latent horizontal fea- tures.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Hohonet: 360 indoor holistic understanding with latent horizontal fea- tures

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.728139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.304955Z digest=sha256:00fd32d2210e1bdabc3cfa424815d8bbbf35a55541550f71c99a61bef5748fd3

Observation 0e96af74-1191-4b10-a8fe-57b5c240646f · outbound

This paper cites Hisplat: Hierarchical 3d gaus- sian splatting for generalizable sparse-view reconstruction.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Hisplat: Hierarchical 3d gaus- sian splatting for generalizable sparse-view reconstruction

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.718705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.308175Z digest=sha256:a42c3c65c4b406891b74d3334842a0ba7da16291feb5013c6211dba0ab4ddf3c

Observation 629bba7d-18c1-4bad-b5e9-c4671e4f3256 · outbound

This paper cites Mv-dust3r+: Single-stage scene reconstruction from sparse views in 2 seconds.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Mv-dust3r+: Single-stage scene reconstruction from sparse views in 2 seconds

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.707977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.311519Z digest=sha256:06dd2775e8fab5dc1d21727a6cddeae14ef21d0de8b836a6120fd896880ce86f

Observation 8f32902b-0e77-4f11-9d40-0692b4aad34a · outbound

This paper cites Distortion-aware convolutional filters for dense prediction in panoramic images.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Distortion-aware convolutional filters for dense prediction in panoramic images

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.698299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.314775Z digest=sha256:57d9229d9241f3f5ca517b1d3f167cf5d45d696a6d441d74143d922494edb0a3

Observation 5d6ec5ba-46d7-422f-8957-65dff9997895 · outbound

This paper cites Bifuse: Monocular 360 depth estimation via bi-projection fusion.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Bifuse: Monocular 360 depth estimation via bi-projection fusion

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.688422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.318248Z digest=sha256:cc3754575bf7187f8c027cc43941e8abeb7413835d07f6e8a2c9ac5994c97b96

Observation e17c96c0-730c-4220-be5a-c8bbb9ed129a · outbound

This paper cites 3d reconstruction with spatial memory.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction 3d reconstruction with spatial memory

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.678930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.321494Z digest=sha256:1b216081181ed9b75dba5193cd97bbce7cfed3050e36638ec3f2b260fa418bf5

Observation 4d6542ff-d835-47f6-83cc-71b63a89bc22 · outbound

This paper cites Ibr- net: Learning multi-view image-based rendering.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Ibr- net: Learning multi-view image-based rendering

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.668782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.324641Z digest=sha256:af738df0620b100844d3bfa8aacb925333b97b89b2e1198ee3894a8c2c425480

Observation dd0a544b-e0b3-42bd-84d9-62e67209dd07 · outbound

This paper cites Continuous 3d per- ception model with persistent state.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Continuous 3d per- ception model with persistent state

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.659700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.327868Z digest=sha256:aede62d63014b98c701cc97bab1b7662636f689aea69b247ec8787d33c276486

Observation c0e42c0d-fd26-43b5-9644-a711c8bbdb52 · outbound

This paper cites Dust3r: Geometric 3d vi- sion made easy.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Dust3r: Geometric 3d vi- sion made easy

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.650268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.330847Z digest=sha256:17c79ac16319da40284c44a2875a4c7a1a8331c384b232d122526d4ad9e4f3cf

Observation 2bbf30bf-3d57-4ec7-bf95-8d42726c161d · outbound

This paper cites Looprefine: Deep camera pose estimation with loop consistency.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Looprefine: Deep camera pose estimation with loop consistency

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.641285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.334778Z digest=sha256:5239b08ccaf211ebd77628fb2c62116e6605dfd0f0534672487863a9def91e4e

Observation 66c24636-660a-416c-8870-ce7dca25f835 · outbound

This paper cites Croco v2: Improved cross-view completion pre- training for stereo matching and optical flow.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Croco v2: Improved cross-view completion pre- training for stereo matching and optical flow

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.631881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.337994Z digest=sha256:af1befc99b159b0e9ae5b4a421dcc74e35fba0ce339040d836b468f135c4a44b

Observation f11ca78f-92f1-4cea-bb93-b2c26fc39f95 · outbound

This paper cites Depthsplat: Connecting gaussian splatting and depth.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Depthsplat: Connecting gaussian splatting and depth

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.622439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.341046Z digest=sha256:f5984dfd5c961da7eba13c4930fe60d7088384098cf8807b5ebc62f613d6ce0c

Observation f8260450-ab37-4d4f-86b0-97aae7889ec1 · outbound

This paper cites FreeSplatter: Pose-free Gaussian Splatting for Sparse-view 3D Reconstruction.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction FreeSplatter: Pose-free Gaussian Splatting for Sparse-view 3D Reconstruction

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-06T12:17:22.344418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:22.344418Z digest=sha256:01de326a9653e93776e455ac9c19f8c1107d16c29214ca944781470915ef5e5c

Observation a7c7d863-126d-4ab9-8786-ea99ba43bfeb · outbound

This paper cites Fast3r: Towards 3d reconstruction of 1000+ images in one forward pass.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Fast3r: Towards 3d reconstruction of 1000+ images in one forward pass

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.613221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.347725Z digest=sha256:44996b9b15c09319f0a14ef738050b937bf7cdbc3d9e02662525ae148de69ee0

Observation 156c4d7b-ff45-4bca-8092-8d532110f148 · outbound

This paper cites No pose, no problem: Surprisingly simple 3d gaussian splats from sparse unposed images.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction No pose, no problem: Surprisingly simple 3d gaussian splats from sparse unposed images

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.603883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.351702Z digest=sha256:82298fcbaca0cb0f61fe7c4d3778fbe5b6bc65243f57b24e0b57d189e01e5ca3

Observation 8f7ea072-5aed-4ecf-bed7-36a3aba9e662 · outbound

This paper cites pixelnerf: Neural radiance fields from one or few images.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction pixelnerf: Neural radiance fields from one or few images

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.593842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.354897Z digest=sha256:04ae14506d606b71d5b9d93aba4acce75d0e59ed9af075db9ade1d6bc7d6ab68

Observation bd037148-0b13-4157-8d2d-d7de43eb6f77 · outbound

This paper cites Panelnet: Understanding 360 indoor environment via panel representation.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Panelnet: Understanding 360 indoor environment via panel representation

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.583757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.357977Z digest=sha256:303df6229a7877b8e1469f4c1395ed6ccf54cbcd989cca93020ff2ab52ddf60b

Observation 1718a443-94b0-4fca-9eec-6a83062b7fbd · outbound

This paper cites ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-06T12:17:22.361041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:22.361041Z digest=sha256:6ee0026b0229b8a4574822632988fa3f5bd8695ad8a255838fa79a2a86008beb

Observation 308e18b7-1391-418a-8e2c-c7ed2d6f29f2 · outbound

This paper cites Egformer: Equirectangular geometry- biased transformer for 360 depth estimation.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Egformer: Equirectangular geometry- biased transformer for 360 depth estimation

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.573874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.364344Z digest=sha256:3632fd3401ae199d223977c3da4f48fa111cabe37b069cffe5b6ce531b998171

Observation 4066a0de-ea9b-4e9d-bc8a-611afa17d4d6 · outbound

This paper cites Pansplat: 4k panorama synthesis with feed-forward gaussian splatting.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Pansplat: 4k panorama synthesis with feed-forward gaussian splatting

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.564210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.367557Z digest=sha256:981b0d5812d3cfbc8a55430fcf6d1c4e1afe9b0bec564fe3888672a5e5229c8c

Observation 425d6644-9c25-4e80-947a-8433b3f2df1c · outbound

This paper cites Bending reality: Distortion-aware transformers for adapting to panoramic se- mantic segmentation.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Bending reality: Distortion-aware transformers for adapting to panoramic se- mantic segmentation

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.554155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.370813Z digest=sha256:5f674a3c8b477d8fd2cf9b735d6af83ce0ffa1117188924e00d8b3b896fe76e4

Observation 10cc0482-cd5d-425e-8eb1-20ee3566ce34 · outbound

This paper cites Monst3r: A simple approach for estimating geometry in the presence of motion.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Monst3r: A simple approach for estimating geometry in the presence of motion

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.544043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.373924Z digest=sha256:8d27da4346dddebdda7078128bb13e539e9707522713280dcda5297c63d42f48

Observation 50dfda41-0d2b-4a4a-854e-d5577beb156a · outbound

This paper cites Acdnet: Adaptively combined dilated con- volution for monocular panorama depth estimation.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Acdnet: Adaptively combined dilated con- volution for monocular panorama depth estimation

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-06T12:17:22.377166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:17:22.377166Z digest=sha256:c08e56b4a9be22df0d0f2edccd780451d12d6c3975f68471ebe561a36c5c1b77

Observation ff8a38df-8f79-43c6-97fb-58e28a23cadd · outbound

This paper cites Omnidepth: Dense depth estimation for indoors spherical panoramas.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction Omnidepth: Dense depth estimation for indoors spherical panoramas

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:22.528283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.380837Z digest=sha256:45a16acaca762146c591a809945f6a941591976d423476479c03c97382e8cd87

Observation e240cd7c-cac7-4a4e-b637-0a0c79e25c76 · outbound

This paper cites 2, 5, 6, 7, 13, 14.

PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction 2, 5, 6, 7, 13, 14

Reference 386

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T12:17:23.147643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T12:17:22.137413Z digest=sha256:ea80f59cb0d8f178d364816d9355289a3b391f86a0ac8cc1e6f9f041a494fe3e

Pith citing papers

Observation 448ff9c9-3b32-4099-9ec7-ccfa4ae0e829 · inbound

Genie Sim PanoRecon: Fast Immersive Scene Generation from Single-View Panorama cites this paper.

Genie Sim PanoRecon: Fast Immersive Scene Generation from Single-View Panorama PanoSplatt3R: Leveraging Perspective Pretraining for Generalized Unposed Wide-Baseline Panorama Reconstruction

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:35:52.831250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-10T18:25:15.494462Z digest=sha256:02afd2a715b0f81e8de98227faabcf822a04abd44411d0822b9fced5b87bb368