SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation | Paper Citation Record

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

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation nuScenes: A multimodal dataset for autonomous driving,

Reference 1

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This paper cites Two faces of active learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Two faces of active learning,

Reference 2

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This paper cites One thing one click: A self-training approach for weakly supervised 3D semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation One thing one click: A self-training approach for weakly supervised 3D semantic segmentation,

Reference 3

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Observation 7a88b3d7-68a3-4475-bd48-6be2662dcf1e · outbound

This paper cites SemanticKITTI: A dataset for semantic scene understanding of LiDAR sequences,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation SemanticKITTI: A dataset for semantic scene understanding of LiDAR sequences,

Reference 4

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Observation bcac0a9c-b4f4-435c-81b8-990d65474c48 · outbound

This paper cites KPConv: Flexible and deformable convolution for point clouds,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation KPConv: Flexible and deformable convolution for point clouds,

Reference 5

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Observation baa7d8b4-f40f-42b9-b096-14d2975cb914 · outbound

This paper cites Unsupervised multi-task feature learning on point clouds,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Unsupervised multi-task feature learning on point clouds,

Reference 6

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This paper cites Self-supervised learning of local features in 3D point clouds,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Self-supervised learning of local features in 3D point clouds,

Reference 7

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Observation 83cd3201-eb64-4138-a1d2-4443518aacca · outbound

This paper cites Unsupervised point cloud representation learning by clustering and neural rendering,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Unsupervised point cloud representation learning by clustering and neural rendering,

Reference 8

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This paper cites Self-Supervised Pretraining of 3D Features on any Point-Cloud.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Self-Supervised Pretraining of 3D Features on any Point-Cloud

Reference 9

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Observation a3d3bd74-dc93-4aa0-bd81-0e5c774ae594 · outbound

This paper cites Fusion-then- distillation: Toward cross-modal positive distillation for domain adaptive 3D semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Fusion-then- distillation: Toward cross-modal positive distillation for domain adaptive 3D semantic segmentation,

Reference 10

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Observation 9efecbca-0a74-4f71-b833-06bc3001c743 · outbound

This paper cites 3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation 3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving

Reference 11

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Observation 55d0ae7a-32b3-4499-8026-57dd47a505e1 · outbound

This paper cites 4D spatio-temporal ConvNets: Minkowski convolutional neural networks,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation 4D spatio-temporal ConvNets: Minkowski convolutional neural networks,

Reference 12

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Observation 833a0c77-2120-4623-9a21-9ae0748c9d99 · outbound

This paper cites Multi-class active learning for image classification,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Multi-class active learning for image classification,

Reference 13

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Observation 76d6bd0d-2a16-4262-bbba-c54ddd953e5a · outbound

This paper cites Searching efficient 3D architectures with sparse point-voxel convolution,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Searching efficient 3D architectures with sparse point-voxel convolution,

Reference 14

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This paper cites A dataset for semantic scene understanding of LiDAR sequences,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation A dataset for semantic scene understanding of LiDAR sequences,

Reference 15

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This paper cites Gaussian Mixture Models,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Gaussian Mixture Models,

Reference 16

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This paper cites Least squares quantization in PCM,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Least squares quantization in PCM,

Reference 17

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Observation 3a7d8c4c-06dd-4d6b-9def-634cf9ce4925 · outbound

This paper cites k-means++: The advantages of careful seeding,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation k-means++: The advantages of careful seeding,

Reference 18

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Observation d8da43ee-5ec5-46c0-9a33-83f78cad376b · outbound

This paper cites Class- imbalanced semi-supervised learning for large-scale point cloud semantic segmentation via decoupling optimization,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Class- imbalanced semi-supervised learning for large-scale point cloud semantic segmentation via decoupling optimization,

Reference 19

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Observation 464a0a97-184d-4a9e-803d-6e3f1a228c81 · outbound

This paper cites SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances

Reference 20

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Observation c09fd80b-6cd3-4b2e-9efc-78d745ef4f27 · outbound

This paper cites Deep learning-based LiDAR point cloud semantic segmentation for robotics: A survey,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Deep learning-based LiDAR point cloud semantic segmentation for robotics: A survey,

Reference 21

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Observation 0c397551-26b4-47cf-8413-19bac8697875 · outbound

This paper cites LiDAR-based urban scene understanding for smart city applications: A review,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation LiDAR-based urban scene understanding for smart city applications: A review,

Reference 22

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This paper cites PointNet++: Deep hierarchical feature learning on point sets in a metric space,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation PointNet++: Deep hierarchical feature learning on point sets in a metric space,

Reference 23

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Observation c1602e82-6ac2-4b38-bf08-e3a263ab99cd · outbound

This paper cites Spatio-temporal self- supervised representation learning for 3D point clouds,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Spatio-temporal self- supervised representation learning for 3D point clouds,

Reference 24

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Observation eb4db8fe-edaf-430d-993e-7f41d1d5b884 · outbound

This paper cites Batch mode active learning and its application to medical image classification,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Batch mode active learning and its application to medical image classification,

Reference 25

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Observation 7b65bb13-313a-4097-8872-838d33799491 · outbound

This paper cites Active learning using pre-clustering,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active learning using pre-clustering,

Reference 26

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Observation 5498d27c-e770-49c0-b6c6-6b3d6b09f924 · outbound

This paper cites Active learning with clustering,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active learning with clustering,

Reference 27

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Observation c3cc21cf-0d2f-459d-93da-e5d01e6e5ae1 · outbound

This paper cites Subspace prototype guidance for mitigating class imbalance in point cloud semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Subspace prototype guidance for mitigating class imbalance in point cloud semantic segmentation,

Reference 28

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Observation c33d2d41-8cc6-4daf-ae0d-87bd01bfa2ad · outbound

This paper cites BoxSup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation BoxSup: Exploiting bounding boxes to supervise convolutional networks for semantic segmentation,

Reference 29

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Observation b5d5fc94-c0a7-4729-8071-bf31f153fab9 · outbound

This paper cites Discriminative Active Learning.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Discriminative Active Learning

Reference 30

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This paper cites Active learning literature survey,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active learning literature survey,

Reference 31

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Observation f9f42617-61be-48b9-bba1-c78e5e2f88ed · outbound

This paper cites Cylindrical and asymmetrical 3D convolution networks for LiDAR segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Cylindrical and asymmetrical 3D convolution networks for LiDAR segmentation,

Reference 32

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This paper cites A survey of deep active learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation A survey of deep active learning,

Reference 33

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Observation 62ab8a3c-fa0b-4171-94e3-bcc9a8d16307 · outbound

This paper cites 3D spatial recognition without spatially labeled 3D,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation 3D spatial recognition without spatially labeled 3D,

Reference 34

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This paper cites A sequential algorithm for training text classifiers: Corrigendum and additional data,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation A sequential algorithm for training text classifiers: Corrigendum and additional data,

Reference 35

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Observation 45e87ffe-eb19-432a-8f34-fb42735af263 · outbound

This paper cites A new active labeling method for deep learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation A new active labeling method for deep learning,

Reference 36

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This paper cites Margin-based active learning for structured output spaces,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Margin-based active learning for structured output spaces,

Reference 37

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Observation e9de5b41-fe0a-411f-a68e-52ac6f56981d · outbound

This paper cites LADA: Look-ahead data acquisition via augmentation for deep active learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation LADA: Look-ahead data acquisition via augmentation for deep active learning,

Reference 38

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Observation 2f6e8160-90a0-4375-85c9-e565f59f41d4 · outbound

This paper cites Active learning by feature mixing,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active learning by feature mixing,

Reference 39

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Observation 9ca71a67-8a39-4c98-95e1-a7b01bc5b9c9 · outbound

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SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Heterogeneous uncertainty sampling for supervised learning,

Reference 40

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Observation ca0b67bd-c768-486e-b52e-860c67215355 · outbound

This paper cites SQN: Weakly- supervised semantic segmentation of large-scale 3D point clouds,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation SQN: Weakly- supervised semantic segmentation of large-scale 3D point clouds,

Reference 41

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Observation 7fa35552-078d-4c61-b3f9-df14968d7cd7 · outbound

This paper cites Bayesian generative active deep learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Bayesian generative active deep learning,

Reference 42

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This paper cites BaSAL: Size-balanced active learning for LiDAR semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation BaSAL: Size-balanced active learning for LiDAR semantic segmentation,

Reference 45

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Observation d7f53286-32c8-44b9-9f57-b61fa5e9323b · outbound

This paper cites Melnikov Method for Perturbed Completely Integrable Systems.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Melnikov Method for Perturbed Completely Integrable Systems

Reference 46

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Observation 09b3acd2-30db-4b90-bc6e-905bb5fd66b2 · outbound

This paper cites Active learning for point cloud semantic segmentation via spatial-structural diversity reasoning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active learning for point cloud semantic segmentation via spatial-structural diversity reasoning,

Reference 47

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This paper cites Box2Mask: Weakly supervised 3D semantic instance segmentation using bounding boxes,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Box2Mask: Weakly supervised 3D semantic instance segmentation using bounding boxes,

Reference 48

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Observation 270ce453-1577-4741-80e0-3d5a8ca068d4 · outbound

This paper cites REDAL: Region-based and diversity-aware active learning for point cloud semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation REDAL: Region-based and diversity-aware active learning for point cloud semantic segmentation,

Reference 49

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Observation fe8fabb8-7742-4cdd-8da9-5d43292a8d18 · outbound

This paper cites Exploring active 3D object detection from a generalization perspective,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Exploring active 3D object detection from a generalization perspective,

Reference 50

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Observation 133a2e5e-ded2-4a90-bbae-37edf97e9905 · outbound

This paper cites VMNet: V oxel-mesh network for geodesic-aware 3D semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation VMNet: V oxel-mesh network for geodesic-aware 3D semantic segmentation,

Reference 51

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Observation d2a1fa21-1ef2-4262-a735-c77cfd15ed7a · outbound

This paper cites JSENet: Joint semantic segmentation and edge detection network for 3D point clouds,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation JSENet: Joint semantic segmentation and edge detection network for 3D point clouds,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.968234Z

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Observation fb16004d-0b8a-4d3c-860d-2b66212aba51 · outbound

This paper cites Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark

Reference 53

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This paper cites Multiple-instance active learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Multiple-instance active learning,

Reference 54

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This paper cites Active learning with statistical models,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active learning with statistical models,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.941327Z

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Observation 05314828-f3d4-4dec-b987-4718e3b5420f · outbound

This paper cites Efficient learning on point clouds with basis point sets,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Efficient learning on point clouds with basis point sets,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.927665Z

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Observation 74ba5f0f-5112-4156-91bd-f5e4c7b84595 · outbound

This paper cites Multi-path region mining for weakly supervised 3D semantic segmentation on point clouds,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Multi-path region mining for weakly supervised 3D semantic segmentation on point clouds,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.913877Z

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Observation 44d070f9-853c-47c3-ad89-3db0cc9c2438 · outbound

This paper cites Divergence measures based on the Shannon entropy,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Divergence measures based on the Shannon entropy,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.900182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b9db14ba-79af-4380-81b0-2da182047a90 · outbound

This paper cites GroupContrast: Semantic-aware self-supervised representation learning for 3D understanding,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation GroupContrast: Semantic-aware self-supervised representation learning for 3D understanding,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.886981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 620ed7d9-7a3a-43f0-a0b3-0900708e8b8b · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T23:47:40.895485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c10a8bd4-19c4-4bec-be0d-3509d18a13bc · outbound

This paper cites DeepCore: A comprehensive library for coreset selection in deep learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation DeepCore: A comprehensive library for coreset selection in deep learning,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.873552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 89b34007-7e51-4e4f-bfaf-ba3d8b31a46f · outbound

This paper cites Active learning through density clustering,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active learning through density clustering,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.859988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6c7ab9b5-019e-4935-99c5-cefe41085cd5 · outbound

This paper cites Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-15T23:47:40.907761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2660b2c-4603-42f2-8613-48a3250b8930 · outbound

This paper cites Localization-aware active learning for object detection,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Localization-aware active learning for object detection,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.845295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0e772983-04f8-40c5-b11b-35ca49a62587 · outbound

This paper cites Annotating object instances with a Polygon-RNN,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Annotating object instances with a Polygon-RNN,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.830023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d709ce9f-ba4d-4b00-bdba-4365044fe6f5 · outbound

This paper cites Uncertainty in deep learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Uncertainty in deep learning,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.816216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7c817163-c598-4518-b8c6-d4546b6732f0 · outbound

This paper cites Demystifying multi- faceted video summarization: Tradeoff between diversity, representation, coverage and importance,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Demystifying multi- faceted video summarization: Tradeoff between diversity, representation, coverage and importance,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.801839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 185b2c05-5c73-4bed-ae74-10fb6ec5ab17 · outbound

This paper cites An analysis of approximations for maximizing submodular set functions—I,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation An analysis of approximations for maximizing submodular set functions—I,

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.786907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6a804503-60aa-4748-ae88-71bdd3a1fcdf · outbound

This paper cites Bayesian Active Learning for Classification and Preference Learning.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Bayesian Active Learning for Classification and Preference Learning

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T23:47:40.932863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b73b427b-0ab0-4131-8e40-d5148347e22e · outbound

This paper cites Scalable active learning for object detection,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Scalable active learning for object detection,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.772623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e79792ec-0ff8-4fe3-8f42-f2f94b2dfe8a · outbound

This paper cites Submodularity In Machine Learning and Artificial Intelligence.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Submodularity In Machine Learning and Artificial Intelligence

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-15T23:47:40.941197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3a3ac0e-7cbb-453e-92ae-f1843a35846c · outbound

This paper cites Kecor: Kernel coding rate maximization for active 3D object detection,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Kecor: Kernel coding rate maximization for active 3D object detection,

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.758176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a710d250-fa3d-4525-88d1-bd3e202687d8 · outbound

This paper cites Prism: A rich class of parameterized submodular information measures for guided data subset selection,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Prism: A rich class of parameterized submodular information measures for guided data subset selection,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.743345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8e5616ca-0db7-4a81-9377-98e5f3011483 · outbound

This paper cites Inconsistency-based data-centric active open-set annotation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Inconsistency-based data-centric active open-set annotation,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.728819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7cca63cc-fbef-4a0a-8992-0fce03ee2f9c · outbound

This paper cites Similar: Submod- ular information measures based active learning in realistic scenarios,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Similar: Submod- ular information measures based active learning in realistic scenarios,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.713960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bb869d66-c9a6-4648-bc7a-0bedc77cf729 · outbound

This paper cites Talisman: Targeted active learning for object detection with rare classes and slices using submodular mutual information,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Talisman: Targeted active learning for object detection with rare classes and slices using submodular mutual information,

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.699254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation dcab2045-823a-4483-906c-7b7c205c8074 · outbound

This paper cites Submodular subset selection for large-scale speech training data,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Submodular subset selection for large-scale speech training data,

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.684645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9d84e15b-5b2a-4d94-ba49-b4f57dca9a5e · outbound

This paper cites Automata: Gradient based data subset selection for compute-efficient hyper-parameter tuning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Automata: Gradient based data subset selection for compute-efficient hyper-parameter tuning,

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.669708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5cea87b3-38ee-4d98-926b-6ad87a4fc039 · outbound

This paper cites GCR: Gradient coreset based replay buffer selection for continual learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation GCR: Gradient coreset based replay buffer selection for continual learning,

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.654755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1df03ff9-bfd5-400a-b517-f00d77944471 · outbound

This paper cites Deep similarity-based batch mode active learning with exploration- exploitation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Deep similarity-based batch mode active learning with exploration- exploitation,

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.640430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3466c12a-4ec5-4939-86e6-68b42335d954 · outbound

This paper cites Batch Active Learning Using Determinantal Point Processes.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Batch Active Learning Using Determinantal Point Processes

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-15T23:47:40.983005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a10a816a-5647-40df-9793-695d01aa3883 · outbound

This paper cites A mathematical theory of communication,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation A mathematical theory of communication,

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.624897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e802536d-9388-40f3-96cd-06b1473436ab · outbound

This paper cites SUN RGB-D: A RGB-D scene understanding benchmark suite,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation SUN RGB-D: A RGB-D scene understanding benchmark suite,

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.610973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 16464119-06ca-4886-b75c-660126539fca · outbound

This paper cites Annotator: A generic active learning baseline for LiDAR semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Annotator: A generic active learning baseline for LiDAR semantic segmentation,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.594532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 88e05ec8-714e-4d67-a89f-7e8ac47f2a09 · outbound

This paper cites Are we hungry for 3D LiDAR data for semantic segmentation? A survey of datasets and methods,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Are we hungry for 3D LiDAR data for semantic segmentation? A survey of datasets and methods,

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.580956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 518186f5-bbce-411e-a7a6-51f3266d121f · outbound

This paper cites Towards 3D LiDAR-based semantic scene understanding of 3D point cloud sequences: The SemanticKITTI Dataset,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Towards 3D LiDAR-based semantic scene understanding of 3D point cloud sequences: The SemanticKITTI Dataset,

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.566817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 03676bd3-59ad-419f-9564-3a859d6eb22d · outbound

This paper cites SECOND: Sparsely embedded convolutional detection,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation SECOND: Sparsely embedded convolutional detection,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.552517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 581ff59c-8efe-4428-a119-5ddc9dd99c4e · outbound

This paper cites LESS: Label-efficient semantic segmentation for LiDAR point clouds,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation LESS: Label-efficient semantic segmentation for LiDAR point clouds,

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.538193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3ace750f-ebaa-49a9-951f-3b73c2a53a19 · outbound

This paper cites Multi-class active learning for image classification,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Multi-class active learning for image classification,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.523854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 369196f4-bee8-4f96-8c4e-a6eb1af4b752 · outbound

This paper cites Cost-effective active learning for deep image classification,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Cost-effective active learning for deep image classification,

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.509192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 599dea93-e65c-43c8-b402-c2c66bc855b4 · outbound

This paper cites The power of ensembles for active learning in image classification,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation The power of ensembles for active learning in image classification,

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.494293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0d1e5b66-08e9-4e19-b38a-b14956f61bd6 · outbound

This paper cites A multi-granularity semi- supervised active learning for point cloud semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation A multi-granularity semi- supervised active learning for point cloud semantic segmentation,

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.479665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7b75d125-608e-44f6-8f88-336cc7ba3165 · outbound

This paper cites Making Your First Choice: To Address Cold Start Problem in Vision Active Learning.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Making Your First Choice: To Address Cold Start Problem in Vision Active Learning

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-15T23:47:41.032170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d649038-adcd-4d95-8334-12a068772177 · outbound

This paper cites Addressing the item cold-start problem by attribute-driven active learning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Addressing the item cold-start problem by attribute-driven active learning,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.466522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6df9f872-f052-4354-9472-eb9bcde1b0f7 · outbound

This paper cites Cold-start active learning with robust ordinal matrix factorization,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Cold-start active learning with robust ordinal matrix factorization,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.453023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 05792d89-7443-4147-84b3-a0bbc5b6d3ad · outbound

This paper cites Gaussian mixture models,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Gaussian mixture models,

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.438368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4ca10605-61ea-4a5f-9883-2a55e0d4a86a · outbound

This paper cites Active learning for point cloud semantic segmentation via spatial-structural diversity reasoning,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active learning for point cloud semantic segmentation via spatial-structural diversity reasoning,

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.424793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d8e759ba-cd14-4974-ab61-f12c0b782083 · outbound

This paper cites LIDAL: Inter-frame uncertainty based active learning for 3D LiDAR semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation LIDAL: Inter-frame uncertainty based active learning for 3D LiDAR semantic segmentation,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.409614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d4f9b01d-3cab-48b1-b7f1-9441daf00f77 · outbound

This paper cites Active learning for deep detection neural networks,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Active learning for deep detection neural networks,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.394091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d803664b-ab90-4dc9-855f-da356a4e52d0 · outbound

This paper cites STONE: A Submodular Optimization Framework for Active 3D Object Detection.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation STONE: A Submodular Optimization Framework for Active 3D Object Detection

Reference 100

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:47:41.152376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6dd997f7-b394-4742-a455-3d03419458b8 · outbound

This paper cites ViewAL: Active learning with viewpoint entropy for semantic segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation ViewAL: Active learning with viewpoint entropy for semantic segmentation,

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.380739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4faa8dab-2cb3-49c8-b960-dba09b34f542 · outbound

This paper cites Suggestive annotation: A deep active learning framework for biomedical image segmentation,.

SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation Suggestive annotation: A deep active learning framework for biomedical image segmentation,

Reference 102

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:47:41.365795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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