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Paper Citation Record · LEDGER

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction

As of 14 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2412.07616.

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

pith.paper-citation-record.v1
2412.07616 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:43:35.061427Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

43 of 43 outbound references displayed

  • verified exact1
  • verified fuzzy35
  • unresolved7
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 65f4c73b-6148-4f72-99fe-60c8abf07930 · outbound

This paper cites PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 72b30039-660b-4fcf-ae70-6b615099ace3 · outbound

This paper cites 3d object detection with pointformer.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction 3d object detection with pointformer

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation cdecd08e-9e4b-4203-a8e4-44a2fb8cadf9 · outbound

This paper cites Lif-seg: Lidar and camera image fusion for 3d lidar semantic segmentation.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Lif-seg: Lidar and camera image fusion for 3d lidar semantic segmentation

Reference 3

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation b9a58e47-57d0-4701-b5a1-425bec7ba9ea · outbound

This paper cites Partner: Level up the polar representa- tion for lidar 3d object detection, 2023.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Partner: Level up the polar representa- tion for lidar 3d object detection, 2023

Reference 4

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 19ee4d46-8d34-4841-bfb6-99457f76eafe · outbound

This paper cites Deep learning-enabled 3d multimodal fusion of cone-beam ct and intraoral mesh scans for clinically applica- ble tooth-bone reconstruction.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Deep learning-enabled 3d multimodal fusion of cone-beam ct and intraoral mesh scans for clinically applica- ble tooth-bone reconstruction

Reference 5

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raw_fallback, observed 2026-08-11T18:43:36.719534Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 2636c143-3335-47ca-b75c-1dca117d1acb · outbound

This paper cites Center- based 3d object detection and tracking.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Center- based 3d object detection and tracking

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0fa83dfe-2bae-4171-9dc5-862ebd45533b · outbound

This paper cites 3d semantic segmentation with submani- fold sparse convolutional networks.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction 3d semantic segmentation with submani- fold sparse convolutional networks

Reference 7

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raw_fallback, observed 2026-08-11T18:43:36.648031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.479135Z digest=sha256:0e481c42ec65f6be72ea468e16e001e92f7e1a4c9b760ed683ff9762d4d7ee4b

Observation b09de13a-93a2-4d13-b4f6-a4d5ad53701c · outbound

This paper cites Segcloud: Semantic segmen- tation of 3d point clouds.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Segcloud: Semantic segmen- tation of 3d point clouds

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.500967Z digest=sha256:a403637ef7436c0c7c590fda2799010331c2419f72c29a3fa7cabb695f271318

Observation 5e3fe7a0-9dd0-42ad-b2cb-7a55bb6c2418 · outbound

This paper cites Mseg3d: Multi-modal 3d semantic segmentation for autonomous driv- ing.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Mseg3d: Multi-modal 3d semantic segmentation for autonomous driv- ing

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.523241Z digest=sha256:c2a097d3c253e72423e09b23240a0de123a6a2ae5f1c477fdad0e01218b1f698

Observation b41996c8-2702-4f6f-a1f1-36f653bf4119 · outbound

This paper cites Hydro-3d: Hybrid object detection and tracking for co- operative perception using 3d lidar.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Hydro-3d: Hybrid object detection and tracking for co- operative perception using 3d lidar

Reference 10

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5068ec07-b8e8-4a17-98c2-752aab399b93 · outbound

This paper cites Supfusion: Supervised lidar- camera fusion for 3d object detection.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Supfusion: Supervised lidar- camera fusion for 3d object detection

Reference 11

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.568083Z digest=sha256:76a905b60bff3ce2bec9b2129961a86df3f7f0d34d79037b1f3c58193c1cfcb6

Observation 41281ff8-c730-4452-8cf1-5876bd2e317c · outbound

This paper cites AI-enabled Automatic Multimodal Fusion of Cone-Beam CT and Intraoral Scans for Intelligent 3D Tooth-Bone Reconstruction and Clinical Applications.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction AI-enabled Automatic Multimodal Fusion of Cone-Beam CT and Intraoral Scans for Intelligent 3D Tooth-Bone Reconstruction and Clinical Applications

Reference 12

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no resolver link, observed 2026-08-11T18:43:34.624964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:43:34.624964Z digest=sha256:250bb6ffd86e9609b990bbbd309bd93a33bea28dfd58ced59d72e2a033ef9c2c

Observation 3fab6b7e-d6e2-4ad0-9c2c-5065d3b8f840 · outbound

This paper cites Refined individual tooth segmentation from cone beam ct images.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Refined individual tooth segmentation from cone beam ct images

Reference 13

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raw_fallback, observed 2026-08-11T18:43:36.355370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.660790Z digest=sha256:1929d00de48ede10d2cd1a540f408fa244d1ecbc2684b629fbc2be3cb932b9ba

Observation 8fd73c06-5b0d-4ceb-b905-da45ca044266 · outbound

This paper cites Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:43:34.697182Z digest=sha256:24435bde62739d19338bd79149a328b80f7997b7097e3c81a18c66499663cc09

Observation 879acb63-a424-451a-8963-7b1e352ec05b · outbound

This paper cites OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction

Reference 15

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no resolver link, observed 2026-08-11T18:43:34.722751Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:43:34.722751Z digest=sha256:3e31405657d308e7a4df796be3d47f368853d23b93ddb12b4b6aa2838b0adfbb

Observation 4d78403a-e1a8-4e1d-bff9-2f804892819e · outbound

This paper cites Openoccupancy: A large scale benchmark for sur- rounding semantic occupancy perception.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Openoccupancy: A large scale benchmark for sur- rounding semantic occupancy perception

Reference 16

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 8ad61ce0-f9ef-46e8-a6b0-829d919b712b · outbound

This paper cites SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving

Reference 17

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source=pdf_text observed=2026-08-11T18:43:34.731798Z digest=sha256:2ff9b27c244b5cf9294eec85a389f0b727b414670a3f3ff0e757d02eba267af8

Observation 7533e152-a1a9-4af3-82e5-c2d3de82fe44 · outbound

This paper cites Scalable geometric fracture assembly via co-creation space among assemblers.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Scalable geometric fracture assembly via co-creation space among assemblers

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 41705354-3392-4f74-9fb1-37ee80d2d0d5 · outbound

This paper cites Sa-convonet: Sign-agnostic optimization of convolutional occupancy networks.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Sa-convonet: Sign-agnostic optimization of convolutional occupancy networks

Reference 19

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raw_fallback, observed 2026-08-11T18:43:36.191026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 27da0f3a-6b10-4f5d-aa6f-1c5447772707 · outbound

This paper cites Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers, 2022.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers, 2022

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 9a4ba37a-c33b-4ae9-856e-63e0f2d2847f · outbound

This paper cites Feature pyra- mid networks for object detection.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Feature pyra- mid networks for object detection

Reference 21

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.749226Z digest=sha256:7bdb98bab463928bd99ad24bcfa625314c7c7450a8832373a8cf8fbcae8d8f38

Observation 795c91ed-1f09-4173-832f-68e7b7769014 · outbound

This paper cites Polarformer: Multi- camera 3d object detection with polar transformer.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Polarformer: Multi- camera 3d object detection with polar transformer

Reference 22

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raw_fallback, observed 2026-08-11T18:43:35.965704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.753657Z digest=sha256:c5abb2f3bf17f12f41853eaecd4cc9dc421235749175e1a925f6424eeedd695b

Observation 865be536-788e-48cc-b4a9-ed2bb45aedcc · outbound

This paper cites Craft: Camera-radar 3d object detection with spatio-contextual fusion transformer.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Craft: Camera-radar 3d object detection with spatio-contextual fusion transformer

Reference 23

Resolution
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raw_fallback, observed 2026-08-11T18:43:35.932113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.758971Z digest=sha256:e7a6ca8c69f60fd82bf7cecc31773d1b4e50b2a7bf8605b562478c7a92df7dfe

Observation 289b0b20-e13a-4c29-b6a7-0d213186390d · outbound

This paper cites Semantic seg- mentation of 3d lidar data using deep learning: a re- view of projection-based methods.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Semantic seg- mentation of 3d lidar data using deep learning: a re- view of projection-based methods

Reference 24

Resolution
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raw_fallback, observed 2026-08-11T18:43:35.916763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0546ad36-d216-4638-961a-4b480b53383e · outbound

This paper cites Polarpoint-bev: Bird-eye- view perception in polar points for explainable end-to-end autonomous driving.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Polarpoint-bev: Bird-eye- view perception in polar points for explainable end-to-end autonomous driving

Reference 25

Resolution
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raw_fallback, observed 2026-08-11T18:43:35.902118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.768184Z digest=sha256:ab9ba7fd8b55294673070cb94e5ef8d67be161c80e5969a0ed6def7f9ec85c53

Observation 39ddea1a-9dcd-4723-91f9-074daae9b4da · outbound

This paper cites Polarnet: An improved grid representation for online lidar point clouds se- mantic segmentation.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Polarnet: An improved grid representation for online lidar point clouds se- mantic segmentation

Reference 26

Resolution
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raw_fallback, observed 2026-08-11T18:43:35.884715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.772683Z digest=sha256:1f7e4db1025d152ff0ad799b5b27abdeaae4cde5cbb6abfbb0a21c7d00a48996

Observation d807d8f0-9501-4320-a054-499f9a0cf87e · outbound

This paper cites Cylindrical and asymmetrical 3d convolution networks for lidar segmenta- tion.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Cylindrical and asymmetrical 3d convolution networks for lidar segmenta- tion

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:43:35.795758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.777589Z digest=sha256:60c1ab0e3a82c6d351f3bd3118bde79b2ac606abfb0092bde25bfab4af4b0d61

Observation a95ec2b1-8247-44e9-9695-e7824c605fe0 · outbound

This paper cites Polarstream: Streaming object detection and segmentation with polar pil- lars.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Polarstream: Streaming object detection and segmentation with polar pil- lars

Reference 28

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raw_fallback, observed 2026-08-11T18:43:35.731386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.782495Z digest=sha256:8e677075daaa43c85fe014a3cde8c95243631697e789b7b0c57bce893b622444

Observation 61370ecb-b1a8-4eb9-9598-54ed64b8bec8 · outbound

This paper cites One Training for Multiple Deployments: Polar-based Adaptive BEV Perception for Autonomous Driving.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction One Training for Multiple Deployments: Polar-based Adaptive BEV Perception for Autonomous Driving

Reference 29

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local_arxiv, observed 2026-08-11T18:43:35.108350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.787085Z digest=sha256:f9d41bc1cabf9e506dced147fbf3e0cdb34c5cac920f39ae1dc870366cc79217

Observation 8c30c952-b77d-4190-a98c-9cfbae05aa66 · outbound

This paper cites Se- mantickitti: A dataset for semantic scene understanding of lidar sequences, 2019.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Se- mantickitti: A dataset for semantic scene understanding of lidar sequences, 2019

Reference 30

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raw_fallback, observed 2026-08-11T18:43:35.715276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.791922Z digest=sha256:298e06fac4a443a5e8b54e935c7db13ddba862d2a4f11bad8b71077f55b5e51b

Observation 71a74883-6014-4b97-be7f-4d77d6d13810 · outbound

This paper cites Lmscnet: Lightweight multiscale 3d semantic completion,.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Lmscnet: Lightweight multiscale 3d semantic completion,

Reference 31

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raw_fallback, observed 2026-08-11T18:43:35.700697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.796109Z digest=sha256:522b11d75c3f5199cccf04aa2e187e4817573c44e2922fbd3c4d7b973b0976c4

Observation 5470c39e-fb6e-42f1-9b46-6954dae469cd · outbound

This paper cites Sparse single sweep lidar point cloud segmentation via learning contextual shape priors from scene completion, 2021.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Sparse single sweep lidar point cloud segmentation via learning contextual shape priors from scene completion, 2021

Reference 32

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raw_fallback, observed 2026-08-11T18:43:35.685275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.800717Z digest=sha256:5eb48f8c41042a7acb91cd54a66fa55527765d521bd6d8e18852e5c403684413

Observation d8a83b13-78cb-4623-9e62-e6f50edb08de · outbound

This paper cites Anisotropic convolutional networks for 3d semantic scene completion, 2020.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Anisotropic convolutional networks for 3d semantic scene completion, 2020

Reference 33

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raw_fallback, observed 2026-08-11T18:43:35.669815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 4d36fe0e-43fe-44d6-bcc5-f2b671abca86 · outbound

This paper cites Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d, 2020.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d, 2020

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:43:35.569047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.809282Z digest=sha256:9b88009c55fa687b019dd499edfea0f963739002bf559e477a77b7dcaa330dba

Observation a9165779-6c23-4064-bde8-063d1a23ae19 · outbound

This paper cites Deep residual learning for image recognition.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Deep residual learning for image recognition

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T18:43:34.814136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:43:34.814136Z digest=sha256:3f026e5f249dc64d5f78c2c22b28364543e54a877178723ac34b1585b21f89b9

Observation b0d01a94-180e-44a3-b3dc-7939ab9eef90 · outbound

This paper cites Bevfusion: Multi- task multi-sensor fusion with unified bird’s-eye view repre- sentation.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Bevfusion: Multi- task multi-sensor fusion with unified bird’s-eye view repre- sentation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:43:35.475845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e268b5b8-e175-44f5-a750-1e198bffaaac · outbound

This paper cites Scf-net: Learning spatial contextual fea- tures for large-scale point cloud segmentation.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Scf-net: Learning spatial contextual fea- tures for large-scale point cloud segmentation

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:43:35.460893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.860437Z digest=sha256:a700066e17c82713066d588417787e11f34a9a8f2df9c23e567ca714bb22259f

Observation 5e96828a-a87d-4efe-b949-b1958d97fc1d · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction nuscenes: A multi- modal dataset for autonomous driving

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:43:35.442080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.883980Z digest=sha256:47b16e5603cd4d1ab1e59140b2a5a434adb6f7b3308230fbbe91dc9dfd0fea63

Observation 8ebee864-7bfd-4e5c-9567-6baabe5c4362 · outbound

This paper cites Monoscene: Monoc- ular 3d semantic scene completion, 2022.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Monoscene: Monoc- ular 3d semantic scene completion, 2022

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:43:35.424433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.919300Z digest=sha256:1bb534e4f1e2acc937a938cf67ed8e1f76ed3c73bd01ee5d08e53904ebd0539c

Observation c51bdc94-a75e-4bf3-8c0c-3154fbca6944 · outbound

This paper cites 3d sketch-aware semantic scene completion via semi-supervised structure prior, 2020.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction 3d sketch-aware semantic scene completion via semi-supervised structure prior, 2020

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:43:35.405997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.956987Z digest=sha256:27324329f30dcf0466b834848f6eeb295e96a2288d7c47af741f49fed0b29637

Observation 34cf50a1-1dbf-4f36-8f93-f36e50236a39 · outbound

This paper cites Toothsegnet: image degradation meets tooth segmentation in cbct images.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Toothsegnet: image degradation meets tooth segmentation in cbct images

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:43:35.306407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:34.989031Z digest=sha256:e492844869190b73f230c5efe4165e23042383237d8c018af16a621b7a3a459f

Observation cf397384-5cc1-44d7-929e-ab71bbccbf68 · outbound

This paper cites an unresolved cited work.

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-11T18:43:35.221398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:35.023698Z digest=sha256:ec6870f865bf02ca58aa96fdb330608d460fddd2bed70bef4ebdcfa6c1534327

Observation 6e602c2a-e223-4656-bf8a-24b5de1313ae · outbound

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

PVP: Polar Representation Boost for 3D Semantic Occupancy Prediction Swin transformer: Hierarchical vision transformer using shifted windows

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:43:35.205586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T18:43:35.061427Z digest=sha256:65073f60510395a3c305a3cb2b0c0678010ea515db009a32d4ad583dcd62fba3

Pith citing papers

No inbound Pith citation observations are available.