Paper Citation Record · LEDGER

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation

As of 15 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2412.20171.

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

pith.paper-citation-record.v1
2412.20171 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:32:48.267810Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

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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

35 of 35 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7dd256cd-2c98-441c-b7dc-b8309f126fcf · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 1

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Observation 02ebad8f-9c88-4571-91e1-78a425e8fa99 · outbound

This paper cites Overview of environment perception for intelligent vehicles,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Overview of environment perception for intelligent vehicles,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.916578Z

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Observation 78ab7b39-7c58-465c-b1da-0873f64f2c99 · outbound

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

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.898853Z

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Observation ce0791e1-5c5d-4235-819e-15340f8af765 · outbound

This paper cites Fiery: Future instance prediction in bird’s- eye view from surround monocular cameras,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Fiery: Future instance prediction in bird’s- eye view from surround monocular cameras,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.881533Z

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Observation e4a436b4-8839-4c2e-a2e4-efffa960c7cb · outbound

This paper cites St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation St-p3: End-to-end vision-based autonomous driving via spatial-temporal feature learning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.862554Z

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Observation cbf72713-8838-4416-b612-2358c84405e9 · outbound

This paper cites Future directions of intelligent vehicles: Potentials, possibilities, and perspectives,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Future directions of intelligent vehicles: Potentials, possibilities, and perspectives,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.843763Z

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Observation f4830036-b114-4f8c-b2f2-cc3408414bda · outbound

This paper cites Milestones in autonomous driving and intelligent vehicles: Survey of surveys,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Milestones in autonomous driving and intelligent vehicles: Survey of surveys,

Reference 7

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Observation 24c6e118-5282-4532-8243-f15ac37325e8 · outbound

This paper cites ControlVideo: Training-free Controllable Text-to-Video Generation.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation ControlVideo: Training-free Controllable Text-to-Video Generation

Reference 8

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Observation 20a4269e-7bda-4fd2-9c91-adea825cafef · outbound

This paper cites PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

Reference 9

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Observation 13d9ab69-50b7-4ef5-9ce8-4d7a91dac54a · outbound

This paper cites BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

Reference 10

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Observation fb283051-974f-45c9-93de-5b731c34eb93 · outbound

This paper cites Delving deeper into convolutional networks for learning video representations,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Delving deeper into convolutional networks for learning video representations,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.809429Z

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Observation 35e99503-1ba9-4d83-9019-c598e60ddbcc · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation nuscenes: A multimodal dataset for autonomous driving,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.789833Z

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Observation ad137441-3b44-43f7-889f-22117382a740 · outbound

This paper cites The cityscapes dataset for semantic urban scene understanding,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation The cityscapes dataset for semantic urban scene understanding,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.772005Z

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Observation dbd0a0b9-c95d-4a27-9759-c4763f349501 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Are we ready for autonomous driving? the kitti vision benchmark suite,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.753352Z

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Observation 6c873b27-e87c-4547-b4c4-2e9dee5f832f · outbound

This paper cites Cross-view semantic segmentation for sensing surroundings,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Cross-view semantic segmentation for sensing surroundings,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.732629Z

Source-reported events for the cited work

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Observation d5333ada-a0b6-4ae1-ad5f-553a9aa3b4bb · outbound

This paper cites Cross-view transformers for real-time map-view semantic segmentation,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Cross-view transformers for real-time map-view semantic segmentation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.714362Z

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Observation f83d6608-dd73-41a2-b060-e0f1733f5680 · outbound

This paper cites PETR: Position Embedding Transformation for Multi-View 3D Object Detection.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation PETR: Position Embedding Transformation for Multi-View 3D Object Detection

Reference 17

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Observation 831d4d8d-4652-4626-8b71-ce63eb0ad6ed · outbound

This paper cites A closer look at spatiotemporal convolutions for action recognition,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation A closer look at spatiotemporal convolutions for action recognition,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.694454Z

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Observation 2b02a5ff-ec83-4607-94ce-15ba5d13200f · outbound

This paper cites Spatiotemporal multiplier networks for video action recognition,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Spatiotemporal multiplier networks for video action recognition,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.677114Z

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Observation f0d11c0f-1365-4f07-82ee-b82d53ecf11e · outbound

This paper cites Full-duplex strategy for video object segmentation,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Full-duplex strategy for video object segmentation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.660276Z

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Observation 918532f5-a295-4e74-9e1f-39e23184056d · outbound

This paper cites Long short-term memory,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Long short-term memory,

Reference 21

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Observation b033c8c9-b00c-4a73-b4bc-d6e08ed0611b · outbound

This paper cites Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Reference 22

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This paper cites Video panoptic segmentation,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Video panoptic segmentation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.630214Z

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Observation d53ef743-be28-4c7f-a30f-b9d431417cb2 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Pytorch: An imperative style, high-performance deep learning library,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.612395Z

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Observation ed0bdc02-7178-47b3-8a3e-c86706908ec6 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolu- tional neural networks,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Efficientnet: Rethinking model scaling for convolu- tional neural networks,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.592525Z

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Observation 679b0e61-b9d9-4f63-8147-3ac30b0e83c3 · outbound

This paper cites Monocular semantic occupancy grid mapping with convolutional variational encoder– decoder networks,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Monocular semantic occupancy grid mapping with convolutional variational encoder– decoder networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.572637Z

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Observation 24e9ea9a-5a1a-4f01-8704-379d0b9311e3 · outbound

This paper cites Predicting semantic map representations from images using pyramid occupancy networks,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Predicting semantic map representations from images using pyramid occupancy networks,

Reference 27

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Observation bef5b7fe-2d1e-4655-923b-7e8634c2dfbd · outbound

This paper cites Enabling spatio- temporal aggregation in birds-eye-view vehicle estimation,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Enabling spatio- temporal aggregation in birds-eye-view vehicle estimation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.536384Z

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Observation 16dd7c2a-1e62-4da7-8b6d-ade64f823ff9 · outbound

This paper cites FISHING Net: Future Inference of Semantic Heatmaps In Grids.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation FISHING Net: Future Inference of Semantic Heatmaps In Grids

Reference 29

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Observation 99bb04f2-ca1e-4d6b-b6e0-fa7c91b2acb7 · outbound

This paper cites Learning interpretable end-to-end vision-based motion planning for autonomous driving with optical flow distillation,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Learning interpretable end-to-end vision-based motion planning for autonomous driving with optical flow distillation,

Reference 30

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Observation aecc0c22-b444-496b-bddc-c0e9574d7272 · outbound

This paper cites Tada! temporally-adaptive convolutions for video understanding,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Tada! temporally-adaptive convolutions for video understanding,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.496976Z

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Observation bb461d32-c47a-4a34-913e-69957b806471 · outbound

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Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Simvp: Simpler yet better video prediction,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.478301Z

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Observation ad51eb1c-158c-4c1b-9a6f-6f060d1ee6d9 · outbound

This paper cites Convolutional lstm network: A machine learning approach for precipitation nowcasting,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Convolutional lstm network: A machine learning approach for precipitation nowcasting,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.459983Z

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Observation 4b72bdb4-85f1-476f-be4c-8e2b0b14a5b9 · outbound

This paper cites Predrnn: A recurrent neural network for spatiotemporal predictive learning,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Predrnn: A recurrent neural network for spatiotemporal predictive learning,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.442470Z

Source-reported events for the cited work

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Observation f667d281-8919-46f3-8a55-cca96b8f6002 · outbound

This paper cites Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learning,.

Geo-ConvGRU: Geographically Masked Convolutional Gated Recurrent Unit for Bird-Eye View Segmentation Predrnn++: Towards a resolution of the deep-in-time dilemma in spatiotemporal predictive learning,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:32:48.424476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

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