Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving | Paper Citation Record

Observation c19da902-3130-49c3-bda4-4c818ccafb34 · outbound

This paper cites Se- manticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Se- manticKITTI: A Dataset for Semantic Scene Understanding of LiDAR Sequences

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.923923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fc8d5302-638d-469d-8d63-c18d57eb458e · outbound

This paper cites Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Simultaneous Semantic Segmentation and Outlier Detection in Presence of Domain Shift

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.908245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e2c12fd9-2fdf-4ed8-b5fb-d90e78549cd5 · outbound

This paper cites Nieto, Roland Y.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Nieto, Roland Y

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.892478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b3a9fe9e-a357-4e3d-ae0a-d7095dd62863 · outbound

This paper cites The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.872706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 03551cef-3f19-46fb-b349-86ee1c9f324d · outbound

This paper cites Perception datasets for anomaly detec- tion in autonomous driving: A survey.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Perception datasets for anomaly detec- tion in autonomous driving: A survey

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.853560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4357704a-47e2-44d7-90be-e17d29f144c1 · outbound

This paper cites Marius Z ¨ollner.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Marius Z ¨ollner

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.833045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation aae205a6-ea9d-4afc-bac4-96616677e1ba · outbound

This paper cites Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Gi- ancarlo Baldan, and Oscar Beijbom

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.813981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7bbec130-2391-4da4-a5b7-7e1d4face894 · outbound

This paper cites Open-set 3D Object Detection.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Open-set 3D Object Detection

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.797276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e1f2a398-3b52-4d58-84e5-51ab673fdb11 · outbound

This paper cites Chakravarthy, Meghana Reddy Ganesina, Peiyun Hu, Laura Leal-Taixe, Shu Kong, Deva Ramanan, and Aljosa Osep.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Chakravarthy, Meghana Reddy Ganesina, Peiyun Hu, Laura Leal-Taixe, Shu Kong, Deva Ramanan, and Aljosa Osep

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.779179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 30005882-a38b-46df-ac18-1945a5ec8c8c · outbound

This paper cites SegmentMeIfYou- Can: A Benchmark for Anomaly Segmentation.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving SegmentMeIfYou- Can: A Benchmark for Anomaly Segmentation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.760693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f2c66e0d-0c28-4dd4-ae8e-eab50533c936 · outbound

This paper cites Entropy maximization and meta classification for out-of- distribution detection in semantic segmentation.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Entropy maximization and meta classification for out-of- distribution detection in semantic segmentation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.740156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 61cfc3c8-023b-4902-a91e-5b575b221801 · outbound

This paper cites Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.722489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8a54ee1d-a708-47e5-a3cd-693a878fe2b9 · outbound

This paper cites Schwing, Alexan- der Kirillov, and Rohit Girdhar.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Schwing, Alexan- der Kirillov, and Rohit Girdhar

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.704419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e180e4b0-7268-412d-8c43-283ca4b600f0 · outbound

This paper cites Schwing, and Alexander Kir- illov.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Schwing, and Alexander Kir- illov

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.685397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c3574ce9-5e87-4eb7-86ee-524c393ff014 · outbound

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

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving The cityscapes dataset for semantic urban scene understanding

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T01:06:37.309707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de9611b3-e1a1-4e10-9d78-1a184b71c3f6 · outbound

This paper cites Outlier detec- tion by ensembling uncertainty with negative objectness.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Outlier detec- tion by ensembling uncertainty with negative objectness

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.654648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 123459ad-88b4-4d1f-b5e6-b8144f34f672 · outbound

This paper cites V os: Learning what you don’t know by virtual outlier synthe- sis.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving V os: Learning what you don’t know by virtual outlier synthe- sis

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.638593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 24c824c4-e4ad-406b-a55f-39650378b870 · outbound

This paper cites Segmenting Known Objects and Unseen Unknowns without Prior Knowledge.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Segmenting Known Objects and Unseen Unknowns without Prior Knowledge

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.622168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7d093510-2b98-4064-9a72-a6d2fcd4a331 · outbound

This paper cites Vision meets robotics: The KITTI dataset.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Vision meets robotics: The KITTI dataset

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.603901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a86b0e52-7cca-4e64-bfbb-c158a177021f · outbound

This paper cites Dense open-set recognition with synthetic outliers generated by Real NVP.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Dense open-set recognition with synthetic outliers generated by Real NVP

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-16T01:06:37.746771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f9338563-3620-4710-96a2-5175b0af90c1 · outbound

This paper cites Densehy- brid: Hybrid anomaly detection for dense open-set recogni- tion.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Densehy- brid: Hybrid anomaly detection for dense open-set recogni- tion

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.586278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6e0b195c-8023-4d73-b159-5c874b4532b0 · outbound

This paper cites Madhava Krishna.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Madhava Krishna

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.564249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b88693fc-7d39-408b-b7ed-f496fd8a4bac · outbound

This paper cites SODA10M: A Large- Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving SODA10M: A Large- Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.543964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 37041051-9e06-4db0-86c9-fb01cf1d2783 · outbound

This paper cites A Baseline for Detect- ing Misclassified and Out-of-Distribution Examples in Neu- ral Networks.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving A Baseline for Detect- ing Misclassified and Out-of-Distribution Examples in Neu- ral Networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.523943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dd72b84d-be20-4071-af22-8e7cc81812d5 · outbound

This paper cites Scaling Out-of-Distribution Detection for Real- World Settings.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Scaling Out-of-Distribution Detection for Real- World Settings

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.506258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation da63eaa8-30ad-4603-88da-8598a788a958 · outbound

This paper cites Scaling out-of-distribution detection for real- world settings.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Scaling out-of-distribution detection for real- world settings

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.488265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0c3f7cf9-cc76-49ac-8304-ab5d37d8f822 · outbound

This paper cites Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.469466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a6fe55db-0126-42eb-bbd8-91e45e6f8b2a · outbound

This paper cites Czarnecki.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Czarnecki

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.450944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3cff76f2-4b24-4a62-b661-c2fed6013f96 · outbound

This paper cites Deepprivacy2: To- wards realistic full-body anonymization.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Deepprivacy2: To- wards realistic full-body anonymization

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.431483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0698e7cd-7e4b-4a3e-8a4d-9329b71e986b · outbound

This paper cites Exemplar-Based Open-Set Panoptic Segmenta- tion Network.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Exemplar-Based Open-Set Panoptic Segmenta- tion Network

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.408947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3c672a41-c8fd-432a-bb2f-20e551b1c018 · outbound

This paper cites Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obsta- cles in Urban-Scene Segmentation.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obsta- cles in Urban-Scene Segmentation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.390056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d509d00d-3277-4d79-b1b1-c893ba2b37e5 · outbound

This paper cites Panoptic Segmentation.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Panoptic Segmentation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.371767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d8d13794-f6b4-429e-9436-48ee2e566d53 · outbound

This paper cites Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Revisiting Out-of-Distribution Detection in LiDAR-based 3D Object Detection

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.354007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c167a7c0-35e0-4f2f-a9e6-cdce2316e595 · outbound

This paper cites Simple and Scalable Predictive Uncertainty Es- timation using Deep Ensembles.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Simple and Scalable Predictive Uncertainty Es- timation using Deep Ensembles

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.337351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8a98ac8b-fc36-47e1-b8f7-ee606b3ad912 · outbound

This paper cites Patch- work++: Fast and robust ground segmentation solving par- tial under-segmentation using 3D point cloud.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Patch- work++: Fast and robust ground segmentation solving par- tial under-segmentation using 3D point cloud

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.321881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bca924f6-7d41-4bae-9564-fb85cdcdeae6 · outbound

This paper cites Coda: A real-world road corner case dataset for object detection in autonomous driving.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Coda: A real-world road corner case dataset for object detection in autonomous driving

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.303824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e1681555-05e3-424b-880d-e7da808af223 · outbound

This paper cites GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.287850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b1e10396-dec5-4fdf-a216-9a98b0502c62 · outbound

This paper cites Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.270529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5bba7d18-caec-4b08-961d-897b8294aa2a · outbound

This paper cites One Million Scenes for Autonomous Driving: ONCE Dataset.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving One Million Scenes for Autonomous Driving: ONCE Dataset

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.254572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 922e0e71-2c42-4d10-9b80-8a2f28c7d8a4 · outbound

This paper cites Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.238400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8407c571-2c03-41a1-a2b1-187209f4b8f7 · outbound

This paper cites Henriques, and Fatma G¨uney.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Henriques, and Fatma G¨uney

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.221938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation adbc1586-dea8-41e5-a8f2-5f025d5bfa10 · outbound

This paper cites OoDIS: Anomaly Instance Segmentation and Detection Benchmark.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving OoDIS: Anomaly Instance Segmentation and Detection Benchmark

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T01:06:37.459091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 626dc0fa-64a3-4f60-a129-0500ed0c69d3 · outbound

This paper cites The mapillary vistas dataset for semantic understanding of street scenes.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving The mapillary vistas dataset for semantic understanding of street scenes

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.206789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation baa6fe09-452b-40eb-af5f-9eb8089e6cb3 · outbound

This paper cites Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.190688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e0d594ea-5173-4325-99f2-fef635fc62a1 · outbound

This paper cites Lost and Found: Detecting Small Road Hazards for Self-Driving Vehicles.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Lost and Found: Detecting Small Road Hazards for Self-Driving Vehicles

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.173547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 1e885889-8903-41ce-85ef-42b9bdf200b8 · outbound

This paper cites LS-VOS: Identifying Outliers in 3D Object Detections Using Latent Space Virtual Outlier Synthesis.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving LS-VOS: Identifying Outliers in 3D Object Detections Using Latent Space Virtual Outlier Synthesis

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.157284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 920de929-48e2-4ea1-8ecd-e118a5793752 · outbound

This paper cites Unmasking Anomalies in Road-Scene Segmentation.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Unmasking Anomalies in Road-Scene Segmentation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.140613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a10512ff-8a78-4458-b1a5-5a6b7f440bc9 · outbound

This paper cites SeMoLi: What Moves Together Belongs Together.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving SeMoLi: What Moves Together Belongs Together

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.122770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d53bdb54-e486-41b0-bf65-b11f2d26bda7 · outbound

This paper cites Madhava Krishna.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Madhava Krishna

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.103885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation dfce9fbd-1c7e-41fb-b4e4-da688ac069a8 · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfitting.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Dropout: a simple way to prevent neural networks from overfitting

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.086474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation fb063956-912f-48ab-8f90-ca3e0cdb02ba · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Scalability in perception for autonomous driving: Waymo open dataset

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.068360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e461132d-edfd-4daf-a59f-353aeb4f710b · outbound

This paper cites Dashcamcleaner: Censor identifiable information in videos from dashcam recordings.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Dashcamcleaner: Censor identifiable information in videos from dashcam recordings

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.049890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 305b3e58-4b72-4736-9c55-f08ecf892868 · outbound

This paper cites The Prevalence of Motor Vehicle Crashes Involving Road Debris, United States, 2011-2014.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving The Prevalence of Motor Vehicle Crashes Involving Road Debris, United States, 2011-2014

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.027128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 51e6d155-8c93-40f5-99df-93c80fbe2c15 · outbound

This paper cites Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Com- plex Urban Driving Scenes.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Com- plex Urban Driving Scenes

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:38.009537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation aafd57a1-7623-4f76-931f-2b21bf676d9f · outbound

This paper cites Panoptic-CUDAL Technical Report: Ru- ral Australia Point Cloud Dataset in Rainy Conditions.arXiv preprint arXiv:2503.16378, 2025.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Panoptic-CUDAL Technical Report: Ru- ral Australia Point Cloud Dataset in Rainy Conditions.arXiv preprint arXiv:2503.16378, 2025

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-16T01:06:37.530521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f00e7ab1-bdb0-4741-8ed7-510f985db9a2 · outbound

This paper cites Verma, J.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Verma, J

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.992659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f1b35da0-6583-43b7-9529-257a985a0360 · outbound

This paper cites KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Ro- bust Registration If Done the Right Way.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Ro- bust Registration If Done the Right Way

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.974212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 67d5220b-df73-4fa2-9fb5-cf5fde84f0ed · outbound

This paper cites Identifying Unknown Instances for Autonomous Driving.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Identifying Unknown Instances for Autonomous Driving

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.957273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 99d0d5c9-9d2c-4293-839d-bb80eecba1a0 · outbound

This paper cites Raod: A benchmark for road abandoned object detection from video surveillance.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Raod: A benchmark for road abandoned object detection from video surveillance

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.937579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f8eaf455-e339-4f9f-8a65-b0af0329368c · outbound

This paper cites Mask4Former: Mask Transformer for 4D Panoptic Segmentation.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Mask4Former: Mask Transformer for 4D Panoptic Segmentation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.917967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation bfe05154-a883-4183-9bae-6a4b0434ffca · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous multitask learning.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Bdd100k: A diverse driving dataset for heterogeneous multitask learning

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.898746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 5f65ebcb-d7bd-4679-ba33-77aa7db846a1 · outbound

This paper cites an unresolved cited work.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-16T01:06:37.879969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7580b3d5-c183-451c-a752-6726ad4bb31a · outbound

This paper cites The point cloud captures the three- dimensional structures of objects at varying distances.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving The point cloud captures the three- dimensional structures of objects at varying distances

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.861853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cdd3f0b5-d504-4f23-a57e-9020bc91a454 · outbound

This paper cites Relation of Performance to Distance and Size We calculated the AP metric for different distance thresh- olds, as shown in Table 4.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Relation of Performance to Distance and Size We calculated the AP metric for different distance thresh- olds, as shown in Table 4

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.840749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9c0db851-bf54-4761-8e13-f82c699b2dc1 · outbound

This paper cites unlabeled.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving unlabeled

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.820661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cee8633c-807d-4fc1-8427-0a373ec67329 · outbound

This paper cites Anomaly points are cyan, unlabeled regions are black, and inliers are pur- ple.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving Anomaly points are cyan, unlabeled regions are black, and inliers are pur- ple

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.801637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 8bc6bbc5-0349-49dc-ab76-5403290b1529 · outbound

This paper cites The other-object class consists of many mis- cellaneous items, including trash bins, advertisement posts, and small pots.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving The other-object class consists of many mis- cellaneous items, including trash bins, advertisement posts, and small pots

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T01:06:37.781635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6a48ad69-f9a7-4fb4-8a66-7e19197d1213 · outbound

This paper cites This also occurred during training runs solely on Panoptic-CUDAL.

Spotting the Unexpected (STU): A 3D LiDAR Dataset for Anomaly Segmentation in Autonomous Driving This also occurred during training runs solely on Panoptic-CUDAL

Reference 68

Resolution: malformed identifier; raw_fallback, observed 2026-08-16T01:06:37.764159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers