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Paper Citation Record · LEDGER

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction

As of 19 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2507.20963.

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

pith.paper-citation-record.v1
2507.20963 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:10:19.700130Z

measured 42 of 42 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

42 of 42 outbound references displayed

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  • verified fuzzy14
  • unresolved27
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Outbound references

Observation c7374141-010a-498b-9f80-ffa1faf65283 · outbound

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

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Cross-view transformers for real-time map-view semantic segmentation,

Reference 1

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Observation 1dfa4372-0044-43bb-ab68-fda120be3e9f · outbound

This paper cites Lidar panoptic segmentation for autonomous driving,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Lidar panoptic segmentation for autonomous driving,

Reference 2

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Observation 3fe4e7c4-d2c1-45ea-b39c-afb2e5e336d3 · outbound

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

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Fiery: future instance prediction in bird’s- eye view from surround monocular cameras,

Reference 3

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Observation b01364aa-ee59-49fd-b97a-81ecd8486927 · outbound

This paper cites Is pseudo- lidar needed for monocular 3d object detection?.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Is pseudo- lidar needed for monocular 3d object detection?

Reference 4

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Observation 25df734d-e7c0-4289-80f9-b43f9842e40a · outbound

This paper cites MMDetection3D: OpenMMLab next-generation platform for general 3D object detection,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction MMDetection3D: OpenMMLab next-generation platform for general 3D object detection,

Reference 5

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Observation 1e90ecda-84f2-4068-85b6-8d561276a44d · outbound

This paper cites MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

Reference 6

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Observation 57f79c23-dccd-47de-b1aa-632fee207775 · outbound

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

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Predicting semantic map representations from images using pyramid occupancy networks,

Reference 7

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Observation 1288bc51-55a3-47cd-bc17-8d3222143c95 · outbound

This paper cites Spatial Pruned Sparse Convolution for Efficient 3D Object Detection.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Spatial Pruned Sparse Convolution for Efficient 3D Object Detection

Reference 8

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Observation 0531a00b-8dfe-4666-8def-4c624ecf95dd · outbound

This paper cites Multi- scale interaction for real-time lidar data segmentation on an embedded platform,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Multi- scale interaction for real-time lidar data segmentation on an embedded platform,

Reference 9

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Observation a7f60da8-91ab-436c-8eff-27b18bf49b9b · outbound

This paper cites OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion

Reference 10

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Observation 31b5f350-4b0e-4f5c-bb66-a245ab55f5e6 · outbound

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

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction

Reference 11

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Observation 1d2b38f5-756f-4ea2-ad60-2814fdb36b5a · outbound

This paper cites OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception

Reference 12

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Observation 56a68fa4-b16e-470b-a27e-f3d8c920d688 · outbound

This paper cites V oxformer: Sparse voxel transformer for camera- based 3d semantic scene completion,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction V oxformer: Sparse voxel transformer for camera- based 3d semantic scene completion,

Reference 13

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Observation 439806da-d21c-403e-89ca-8ea495261a99 · outbound

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

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers,

Reference 14

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Observation 67590b7a-4b4d-4e37-bf6c-26cd78b0ff9b · outbound

This paper cites Let Occ Flow: Self-Supervised 3D Occupancy Flow Prediction.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Let Occ Flow: Self-Supervised 3D Occupancy Flow Prediction

Reference 15

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Observation 4e830e7d-fe74-4173-b551-e1aba64cd519 · outbound

This paper cites Panoocc: Unified occupancy representation for camera-based 3d panoptic segmentation,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Panoocc: Unified occupancy representation for camera-based 3d panoptic segmentation,

Reference 16

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Observation d4d5604d-1b5c-4f61-a7c4-2c311c304f67 · outbound

This paper cites HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction HENet: Hybrid Encoding for End-to-end Multi-task 3D Perception from Multi-view Cameras

Reference 17

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Observation c1a9020e-40b5-4820-a9cc-0f5bae69602c · outbound

This paper cites BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detection.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detection

Reference 18

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Observation 258ef602-6e01-4852-b133-2f98b7494ce5 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Denoising Diffusion Probabilistic Models

Reference 20

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Observation 53445377-b1ec-417e-9c52-9c638e96e9cb · outbound

This paper cites DeTrack: In-model Latent Denoising Learning for Visual Object Tracking.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction DeTrack: In-model Latent Denoising Learning for Visual Object Tracking

Reference 21

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Observation 1e82a5dc-f235-400c-bcc9-f27077a3514e · outbound

This paper cites Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving

Reference 22

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Observation a03adaa1-9580-44d6-8642-8d520feb71f1 · outbound

This paper cites Monoscene: Monocular 3d semantic scene completion,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Monoscene: Monocular 3d semantic scene completion,

Reference 23

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Observation c7dd359f-694c-4c90-9b1e-fbfabddeea96 · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 24

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Observation 6f7e6e98-e4a8-41fd-8f72-11a176c101e2 · outbound

This paper cites DRINet++: Efficient Voxel-as-point Point Cloud Segmentation.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction DRINet++: Efficient Voxel-as-point Point Cloud Segmentation

Reference 25

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Observation cf0aba89-01e4-4ef1-9e61-9408acfecdd3 · outbound

This paper cites Search- ing efficient 3d architectures with sparse point-voxel convolution,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Search- ing efficient 3d architectures with sparse point-voxel convolution,

Reference 26

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Observation b5a952e3-f91e-4b85-8964-dabafbc4555b · outbound

This paper cites Deepvoxels: Learning persistent 3d feature embeddings,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Deepvoxels: Learning persistent 3d feature embeddings,

Reference 27

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Observation 1ac2cb44-4b75-48fc-8693-e62c4f323582 · outbound

This paper cites BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stereo.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction BEVStereo: Enhancing Depth Estimation in Multi-view 3D Object Detection with Dynamic Temporal Stereo

Reference 28

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Observation 5d388c37-6e47-405a-8b7d-541aaada7d42 · outbound

This paper cites BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

Reference 29

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Observation 9e1ce769-8d07-4799-8ffc-ff03fae697a9 · outbound

This paper cites BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection

Reference 30

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Observation 2d5833da-06e8-47c6-9b29-e4e6a6b478de · outbound

This paper cites Fb-bev: Bev representation from forward-backward view transforma- tions,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Fb-bev: Bev representation from forward-backward view transforma- tions,

Reference 31

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Observation e6b0ca9e-0602-41d3-bb94-808e2efe7828 · outbound

This paper cites Bev-lanedet: a simple and effective 3d lane detection baseline,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Bev-lanedet: a simple and effective 3d lane detection baseline,

Reference 32

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Observation 3f179b53-af08-45c0-8b07-880544e8b806 · outbound

This paper cites BEVPoolv2: A Cutting-edge Implementation of BEVDet Toward Deployment.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction BEVPoolv2: A Cutting-edge Implementation of BEVDet Toward Deployment

Reference 33

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Observation b016de49-931b-416e-8d50-60812544b475 · outbound

This paper cites Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View Perception.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View Perception

Reference 34

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Observation 03e0f2ca-9551-4cc6-a983-a4da53212b0f · outbound

This paper cites Focal loss for dense object detection,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Focal loss for dense object detection,

Reference 35

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Observation e6b9a5a9-58f5-4fd7-af79-c421eec93416 · outbound

This paper cites The lov ´asz-softmax loss: A tractable surrogate for the optimization of the intersection- over-union measure in neural networks,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction The lov ´asz-softmax loss: A tractable surrogate for the optimization of the intersection- over-union measure in neural networks,

Reference 36

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 25eac546-1918-418b-98f8-7b30c497bfd8 · outbound

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

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction nuscenes: A multimodal dataset for autonomous driving,

Reference 37

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Observation 16d200ed-55ca-44ae-9ac0-dd417168cd57 · outbound

This paper cites InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions

Reference 38

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Observation 8b27219d-2a9f-4aff-bb94-2ec0b5228384 · outbound

This paper cites Deep residual learning for image recognition,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Deep residual learning for image recognition,

Reference 39

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Observation 83155d89-7887-408e-9f7e-c901a983992e · outbound

This paper cites Improving deep neural networks using softplus units,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Improving deep neural networks using softplus units,

Reference 40

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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 2026-08-19T06:32:44.657259+00:00.

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Observation f1737001-4f76-4b51-bee9-e2db65199c7e · outbound

This paper cites Decoupled Weight Decay Regularization.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Decoupled Weight Decay Regularization

Reference 41

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Observation 2544c67f-1ff2-44ba-b471-dcc678288944 · outbound

This paper cites Fcos3d: Fully convolutional one-stage monocular 3d object detection,.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction Fcos3d: Fully convolutional one-stage monocular 3d object detection,

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-06T13:10:19.931481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 4a3c837c-6787-4cc6-9a22-ab7410776dc1 · outbound

This paper cites PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation.

GTAD: Global Temporal Aggregation Denoising Learning for 3D Semantic Occupancy Prediction PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation

Reference 2023

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Pith citing papers

No inbound Pith citation observations are available.