Paper Citation Record · LEDGER

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models

As of 9 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2507.09216.

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

pith.paper-citation-record.v1
2507.09216 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:07:06.936394Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

29 of 29 outbound references displayed

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verified fuzzy23
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2016a241-5d35-4ce3-8f7e-a5d15a9ef90f · outbound

This paper cites Omnidirectional stereo depth estimation based on spherical deep network,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Omnidirectional stereo depth estimation based on spherical deep network,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:11.908514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1629810e-bef2-4301-87f0-0ad31b5fd25d · outbound

This paper cites Deepsphere: Efficient spherical convolutional neural network with healpix sampling for cosmological applications,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Deepsphere: Efficient spherical convolutional neural network with healpix sampling for cosmological applications,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:11.708364Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ade74500-7007-4285-b372-0189875c9d3d · outbound

This paper cites Both style and distortion matter: Dual-path unsupervised domain adaptation for panoramic semantic segmentation,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Both style and distortion matter: Dual-path unsupervised domain adaptation for panoramic semantic segmentation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:11.221745Z

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Observation 48bd06b2-858f-4ee3-a320-a9351e7bd112 · outbound

This paper cites Look at the neighbor: Distortion-aware unsupervised domain adaptation for panoramic semantic segmentation,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Look at the neighbor: Distortion-aware unsupervised domain adaptation for panoramic semantic segmentation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:11.062086Z

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Observation c0613573-5327-4b76-81e1-fed2c7c1c296 · outbound

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

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Bending reality: Distortion-aware transformers for adapting to panoramic semantic segmentation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:10.933116Z

Source-reported events for the cited work

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Observation b9d2ff40-7914-4c88-b1a1-458a3cd1595f · outbound

This paper cites Single frame semantic segmentation using multi-modal spherical images,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Single frame semantic segmentation using multi-modal spherical images,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:10.710871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9dbf2e5b-2588-49a7-bdac-085ada7ccbd6 · outbound

This paper cites Orientation-aware semantic segmentation on icosahedron spheres,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Orientation-aware semantic segmentation on icosahedron spheres,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:10.574073Z

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Observation 0f6c8b84-ffab-419c-b511-0c2f3db73bed · outbound

This paper cites Tangent images for mitigating spherical distortion,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Tangent images for mitigating spherical distortion,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:10.403440Z

Source-reported events for the cited work

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Observation 38167bdf-8352-4cfc-9776-9420956b4a47 · outbound

This paper cites Spherephd: Applying cnns on a spherical polyhedron representation of 360deg images,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Spherephd: Applying cnns on a spherical polyhedron representation of 360deg images,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:10.150073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7cc70e6d-dd9e-466a-a688-cdd8a72dd260 · outbound

This paper cites Complementary bi-directional feature compression for indoor 360deg semantic segmentation with self-distillation,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Complementary bi-directional feature compression for indoor 360deg semantic segmentation with self-distillation,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:09.993904Z

Source-reported events for the cited work

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Observation a7975417-7a95-4cdc-8bbe-5a33f2d0d3f8 · outbound

This paper cites SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T18:07:04.988810Z

Source-reported events for the cited work

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Observation 7be1d46b-d0d1-4d56-8233-c1d4f5111d4c · outbound

This paper cites Joint 2D-3D-Semantic Data for Indoor Scene Understanding.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Joint 2D-3D-Semantic Data for Indoor Scene Understanding

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T18:07:05.075806Z

Source-reported events for the cited work

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Observation 18bb001c-b6d1-47e9-bb39-c3f61b491dfe · outbound

This paper cites Hohonet: 360 indoor holistic understanding with latent horizontal features,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Hohonet: 360 indoor holistic understanding with latent horizontal features,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:09.797229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f1e2bb35-4ed4-4447-a3f4-0807910aaa59 · outbound

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

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Panoformer: Panorama transformer for indoor 360 depth estimation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:09.625094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3b0d4600-653b-41ac-8545-5ddc06a51f6e · outbound

This paper cites Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:07:07.327697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 27a867bb-842e-44c7-acc3-e494f9dfa600 · outbound

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

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Distortion-aware convolutional filters for dense prediction in panoramic images,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:11.462667Z

Source-reported events for the cited work

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Observation 773404e3-b2ec-4e2d-9087-74819d6a500e · outbound

This paper cites Pass: Panoramic annular semantic segmentation,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Pass: Panoramic annular semantic segmentation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:09.433737Z

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Observation dca3a744-35b8-4a3d-a381-0c9d441b7b03 · outbound

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

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Panelnet: Understanding 360 indoor environment via panel representation,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:09.214479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 327ba232-1c31-45fd-ab19-b3f475ff65ab · outbound

This paper cites Osrt: Omnidirectional image super-resolution with distortion-aware transformer,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Osrt: Omnidirectional image super-resolution with distortion-aware transformer,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:09.074856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f0202436-e7ae-452f-abc8-886240438fd1 · outbound

This paper cites Spherical convolution empowered viewport prediction in 360 video multicast with limited fov feedback,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Spherical convolution empowered viewport prediction in 360 video multicast with limited fov feedback,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:08.817404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 56c826fe-36da-474b-9f10-05c99719d9e6 · outbound

This paper cites Estimating depth of monocular panoramic image with teacher-student model fusing equirectangular and spherical representations,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Estimating depth of monocular panoramic image with teacher-student model fusing equirectangular and spherical representations,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:08.611957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9ed4b1f8-0f7d-48d6-8ab1-a9ce4acdd970 · outbound

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

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Bifuse: Monocular 360 depth estimation via bi-projection fusion,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:08.456421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c9f48d6-cfc6-4016-8c2a-dda548f78e6c · outbound

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

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Unifuse: Unidirectional fusion for 360 panorama depth estimation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:08.291005Z

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Observation dc2e75f9-6c6d-437e-b959-ed016b37e2a2 · outbound

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

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Hrdfuse: Monocular 360deg depth estimation by collaboratively learning holistic-with-regional depth distributions,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:08.008386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5a55637b-ddb4-4a11-8a85-896246792c3b · outbound

This paper cites Deep residual learning for image recognition,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Deep residual learning for image recognition,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T18:07:06.425602Z

Source-reported events for the cited work

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Observation b8cf3e57-16e2-47a6-885f-af28298d3be6 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T18:07:06.525097Z

Source-reported events for the cited work

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Observation 2b77bb92-759c-4917-a23e-442b0e3e09d1 · outbound

This paper cites A convnet for the 2020s,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models A convnet for the 2020s,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:07.809641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 33c28c35-511a-417d-bc8a-c6a4d110ffd2 · outbound

This paper cites 360bev: Panoramic semantic mapping for indoor bird’s-eye view,.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models 360bev: Panoramic semantic mapping for indoor bird’s-eye view,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:07:07.580133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f37ddac7-3bc7-4bc1-ad2e-03661e518fa8 · outbound

This paper cites Spherical CNNs.

360-Degree Full-view Image Segmentation by Spherical Convolution compatible with Large-scale Planar Pre-trained Models Spherical CNNs

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T18:07:06.936394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

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