Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather | Paper Citation Record

Observation 8b9dbd72-1904-4509-9b81-2f7d7c83e2e4 · outbound

This paper cites Invariance principle meets in- formation bottleneck for out-of-distribution generalization.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Invariance principle meets in- formation bottleneck for out-of-distribution generalization

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.703633Z

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Observation 3440cac1-c939-49f2-8b5a-436c92661855 · outbound

This paper cites Deep Variational Information Bottleneck.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Deep Variational Information Bottleneck

Reference 2

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Observation baf6c7af-da94-4f26-a538-7b73740c5c4f · outbound

This paper cites Multi projection fusion for real-time seman- tic segmentation of 3d lidar point clouds.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Multi projection fusion for real-time seman- tic segmentation of 3d lidar point clouds

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.686085Z

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Observation 1598bbc1-5440-4a59-968b-c52a96ebf328 · outbound

This paper cites Rangevit: Towards vision transformers for 3d semantic segmentation in au- tonomous driving.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Rangevit: Towards vision transformers for 3d semantic segmentation in au- tonomous driving

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.668244Z

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Observation 4f1aeb2e-779a-4037-8599-0b258274410b · outbound

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

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Se- mantickitti: A dataset for semantic scene understanding of lidar sequences

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.650629Z

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Observation c037563d-03d4-4293-9eb5-c014f4d79811 · outbound

This paper cites Seeing through fog without seeing fog: Deep multimodal sensor fu- sion in unseen adverse weather.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Seeing through fog without seeing fog: Deep multimodal sensor fu- sion in unseen adverse weather

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.632943Z

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Observation 6522cd62-0e4f-4ed0-b63f-2bb96d0afe9a · outbound

This paper cites 4d spatio-temporal convnets: Minkowski convolutional neural networks.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather 4d spatio-temporal convnets: Minkowski convolutional neural networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.613377Z

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Observation 7cd45caa-617c-4b84-ae0b-7baa436ffb50 · outbound

This paper cites Salsanext: Fast, uncertainty-aware semantic segmentation of lidar point clouds.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Salsanext: Fast, uncertainty-aware semantic segmentation of lidar point clouds

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.595445Z

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Observation 3258b2e1-0232-4429-8de9-230d64331c7e · outbound

This paper cites Incorporating second-order func- tional knowledge for better option pricing.Adv.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Incorporating second-order func- tional knowledge for better option pricing.Adv

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.577614Z

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Observation 70594366-bb12-4642-b81c-550d091840ba · outbound

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

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Are we ready for autonomous driving? the kitti vision benchmark suite

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.559683Z

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Observation 0923e00a-ea0e-4f87-a9b3-3fe965b3521e · outbound

This paper cites 3d semantic segmentation with submanifold sparse convolutional networks.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather 3d semantic segmentation with submanifold sparse convolutional networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.542224Z

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Observation a3c130c0-8e8a-4e91-a475-3f72f33e025a · outbound

This paper cites Deep learning for 3d point clouds: A survey.IEEE Trans.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Deep learning for 3d point clouds: A survey.IEEE Trans

Reference 12

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Observation 194e05af-6344-47bc-9eef-f26741fa0a01 · outbound

This paper cites Fog simulation on real lidar point clouds for 3d object detection in adverse weather.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Fog simulation on real lidar point clouds for 3d object detection in adverse weather

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.513099Z

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Observation fba99720-68ca-4d95-b2a0-fa89ee6b5e02 · outbound

This paper cites Lidar snowfall simulation for robust 3d object detection.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Lidar snowfall simulation for robust 3d object detection

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.495306Z

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Observation b85d3dc8-5e3f-42ba-9887-986bae57210a · outbound

This paper cites Domain generalization-aware uncertainty introspective learning for 3d point clouds segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Domain generalization-aware uncertainty introspective learning for 3d point clouds segmentation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.477350Z

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Observation 3b00167d-8d27-426e-b050-afb9efa71692 · outbound

This paper cites Dual-graph attention convolution network for 3-d point cloud classifi- cation.IEEE Trans.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Dual-graph attention convolution network for 3-d point cloud classifi- cation.IEEE Trans

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.461168Z

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Observation a48035e8-af15-4ee1-a109-072a29196ec7 · outbound

This paper cites Single domain generalization for lidar semantic segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Single domain generalization for lidar semantic segmentation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.443689Z

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Observation db830fe6-49f1-409c-a04e-cc979fbd5178 · outbound

This paper cites Rethinking LiDAR Domain Generalization: Single Source as Multiple Density Domains.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Rethinking LiDAR Domain Generalization: Single Source as Multiple Density Domains

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-07T11:30:15.667228Z

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Observation 02792c1d-a300-4083-a6e6-18184e7f9d9f · outbound

This paper cites Rethinking range view representation for lidar segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Rethinking range view representation for lidar segmentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.424463Z

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Observation 0e5ecdba-029e-4286-bf68-6137ca20dc45 · outbound

This paper cites Robo3d: Towards robust and reliable 3d perception against corruptions.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Robo3d: Towards robust and reliable 3d perception against corruptions

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.406208Z

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Observation f3f9704e-260d-4c8e-b17b-8f306b34ce00 · outbound

This paper cites Stratified trans- former for 3d point cloud segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Stratified trans- former for 3d point cloud segmentation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.388277Z

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Observation 69992cea-43bf-4e15-ae5f-81a9e2aeaafb · outbound

This paper cites Spherical transformer for lidar-based 3d recognition.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Spherical transformer for lidar-based 3d recognition

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.372101Z

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Observation 15791482-6ebe-4563-bf74-0a977e3ad5f9 · outbound

This paper cites Large-scale point cloud semantic segmentation with superpoint graphs.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Large-scale point cloud semantic segmentation with superpoint graphs

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.353954Z

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Observation 83d8e60a-ccf0-4582-b466-f7424bb986cc · outbound

This paper cites 3d- vfield: Adversarial augmentation of point clouds for domain generalization in 3d object detection.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather 3d- vfield: Adversarial augmentation of point clouds for domain generalization in 3d object detection

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.336212Z

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Observation b1bd3e48-ea9b-46b2-b674-d217d5b6a0d7 · outbound

This paper cites Domain generalization with adversarial feature learning.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Domain generalization with adversarial feature learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.319290Z

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Observation 7b9dec4a-fb77-47cc-aabf-fc3af8f54814 · outbound

This paper cites Rapid-seg: Range-aware pointwise distance distribution networks for 3d lidar segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Rapid-seg: Range-aware pointwise distance distribution networks for 3d lidar segmentation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.302446Z

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Observation 2315e0ca-b5f5-4972-a709-7f3a1684377d · outbound

This paper cites Cpgnet: Cascade point-grid fusion network for real-time li- dar semantic segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Cpgnet: Cascade point-grid fusion network for real-time li- dar semantic segmentation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.286589Z

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Observation 7ea6850e-cff4-4ed6-af07-09d4e94f4fdd · outbound

This paper cites Pointcnn: Convolution on x-transformed points.Adv.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Pointcnn: Convolution on x-transformed points.Adv

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.270188Z

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Observation a8c56326-6d28-4971-81a5-e365a1d4c03b · outbound

This paper cites Rangenet++: Fast and accurate lidar semantic segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Rangenet++: Fast and accurate lidar semantic segmentation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.253640Z

Source-reported events for the cited work

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Observation 52403f3b-4204-423f-aa68-50dcf55fb2cd · outbound

This paper cites Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T11:30:15.298202Z

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Observation cc35d367-b420-49e9-a595-ab05a231c8c7 · outbound

This paper cites Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow

Reference 31

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Observation 61adba4c-0870-468e-b4ec-7e916261e635 · outbound

This paper cites V olumetric and multi-view cnns for object classification on 3d data.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather V olumetric and multi-view cnns for object classification on 3d data

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.237972Z

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Observation b6579bfe-6cc4-447a-97a2-cb54b50f1469 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.221358Z

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Observation cb28ff5a-1dcb-47cf-a7f0-ba52c578d542 · outbound

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

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Pointnet++: Deep hierarchical feature learning on point sets in a metric space.Adv

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.204317Z

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Observation 0d392b6d-5107-4f15-b5bb-e4f3b19065f6 · outbound

This paper cites Pointnext: Revisiting pointnet++ with improved training and scaling strategies.Adv.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Pointnext: Revisiting pointnet++ with improved training and scaling strategies.Adv

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.185178Z

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Observation 59236175-cb27-448a-81e2-bfbd26f7c037 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Mobilenetv2: Inverted residuals and linear bottlenecks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.164326Z

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Observation 3a789d02-07b9-45ac-bf0e-1b06d7babc62 · outbound

This paper cites Super-convergence: Very fast training of neural networks using large learning rates.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Super-convergence: Very fast training of neural networks using large learning rates

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.146527Z

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Observation d0973a1a-4a79-4c5b-ae22-07b52ecd5316 · outbound

This paper cites On Efficient Variants of Segment Anything Model: A Survey.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather On Efficient Variants of Segment Anything Model: A Survey

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T11:30:15.338665Z

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Observation 693ad391-f2cf-4efb-96e2-37a14ea17103 · outbound

This paper cites Searching efficient 3d architec- tures with sparse point-voxel convolution.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Searching efficient 3d architec- tures with sparse point-voxel convolution

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.127752Z

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Observation 70be38a2-43f1-47f0-9bee-b828fd7d38f7 · outbound

This paper cites Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results.NeurIPS, 2017.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results.NeurIPS, 2017

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.109332Z

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Observation a0aeb9ad-cf70-42e3-b649-f258cbc70432 · outbound

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

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Kpconv: Flexible and deformable convolution for point clouds

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T11:30:15.352593Z

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Observation ba099299-82eb-4585-8f24-5a8c54fa849e · outbound

This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Instance Normalization: The Missing Ingredient for Fast Stylization

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T11:30:15.357721Z

Source-reported events for the cited work

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Observation adadf53f-8ebc-46a1-b0a9-830a4d4469cf · outbound

This paper cites Attention is all you need.Adv.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Attention is all you need.Adv

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.078060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fb628691-0d14-46b7-ad1c-7a90a6004d62 · outbound

This paper cites Generalizing to unseen domains: A survey on do- main generalization.IEEE Trans.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Generalizing to unseen domains: A survey on do- main generalization.IEEE Trans

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.061735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1a8840bd-d12e-48a2-a62e-504b6105b0a2 · outbound

This paper cites Dynamic graph cnn for learning on point clouds.ACM Trans.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Dynamic graph cnn for learning on point clouds.ACM Trans

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.045677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 68661049-1007-4671-8861-e8357d8ac5e2 · outbound

This paper cites Squeezeseg: Convolutional neural nets with recurrent crf for real-time road-object segmentation from 3d lidar point cloud.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Squeezeseg: Convolutional neural nets with recurrent crf for real-time road-object segmentation from 3d lidar point cloud

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.027451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 53cdad62-b154-44f4-a17c-47182ecb9236 · outbound

This paper cites Pointconv: Deep convolutional networks on 3d point clouds.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Pointconv: Deep convolutional networks on 3d point clouds

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:16.009784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 34c9c118-b702-49f7-bc8f-930be7c98633 · outbound

This paper cites Point transformer v2: Grouped vector atten- tion and partition-based pooling.Adv.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Point transformer v2: Grouped vector atten- tion and partition-based pooling.Adv

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.992616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5094783a-edeb-473d-8e50-dbc31ccbf28e · outbound

This paper cites Point transformer v3: Simpler faster stronger.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Point transformer v3: Simpler faster stronger

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.975901Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 70edb725-a017-45a5-b3fa-1d352d1977d8 · outbound

This paper cites 3d shapenets: A deep representation for volumetric shapes.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather 3d shapenets: A deep representation for volumetric shapes

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.958725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1ad6db43-5b07-49f5-af80-5234f5228f47 · outbound

This paper cites Polarmix: A general data augmen- tation technique for lidar point clouds.Adv.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Polarmix: A general data augmen- tation technique for lidar point clouds.Adv

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.941938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1d4e0466-95d4-4648-85a0-6d9b4e5a2511 · outbound

This paper cites Transfer learning from synthetic to real lidar point cloud for semantic segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Transfer learning from synthetic to real lidar point cloud for semantic segmentation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.925943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 72819e54-5e6a-4ad9-bf29-cfaab78c9547 · outbound

This paper cites 3d semantic segmentation in the wild: Learning generalized models for adverse-condition point clouds.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather 3d semantic segmentation in the wild: Learning generalized models for adverse-condition point clouds

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.908276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4d0fd245-c90f-4088-bba4-d44fac0aae2a · outbound

This paper cites A survey of label-efficient deep learning for 3d point clouds.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather A survey of label-efficient deep learning for 3d point clouds

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.891486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c68f1501-3f9a-4b94-80d0-90fffe93eb76 · outbound

This paper cites Rpvnet: A deep and efficient range-point- voxel fusion network for lidar point cloud segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Rpvnet: A deep and efficient range-point- voxel fusion network for lidar point cloud segmentation

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.871111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7da68f4a-b681-4367-946b-a1352aacdd57 · outbound

This paper cites Benchmarking the robustness of lidar se- mantic segmentation models.Int.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Benchmarking the robustness of lidar se- mantic segmentation models.Int

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.853143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 46c6128d-a70f-490d-9ff9-f4ba662e8360 · outbound

This paper cites Realistic Rainy Weather Simulation for LiDARs in CARLA Simulator.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Realistic Rainy Weather Simulation for LiDARs in CARLA Simulator

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T11:30:15.445834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 331dbfe2-7400-4b18-9e50-5957f1ec1cba · outbound

This paper cites Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T11:30:15.451054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95c6633e-6b7d-4a2a-aa17-5b720b1199d9 · outbound

This paper cites Pcl: Proxy-based contrastive learning for domain generalization.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Pcl: Proxy-based contrastive learning for domain generalization

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.828471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dfd16aea-0dd3-479f-be66-7accbb63c216 · outbound

This paper cites Point transformer.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Point transformer

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.810899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fd70e54f-6f70-4134-9e1a-934cff85cb89 · outbound

This paper cites Unimix: Towards domain adaptive and gener- alizable lidar semantic segmentation in adverse weather.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Unimix: Towards domain adaptive and gener- alizable lidar semantic segmentation in adverse weather

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.792084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 60c90f3f-c184-49ec-8936-983e5caa8473 · outbound

This paper cites Cylinder3d: An effective 3d framework for driving-scene lidar semantic segmentation.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Cylinder3d: An effective 3d framework for driving-scene lidar semantic segmentation

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.767406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4c25bf5f-2358-4fe5-8848-c434e5c00b26 · outbound

This paper cites Domain generalization: A survey.IEEE Trans.

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Domain generalization: A survey.IEEE Trans

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.741295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 674ed36b-8249-4e66-95bd-157a3a37a2dc · outbound

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

Towards Explicit Geometry-Reflectance Collaboration for Generalized LiDAR Segmentation in Adverse Weather Cylindrical and asymmetrical 3d convolution networks for lidar segmenta- tion

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:30:15.722577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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