Paper Citation Record · LEDGER

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties

As of 23 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 3 inbound Pith citation observations for arXiv:2412.14592.

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

pith.paper-citation-record.v1
2412.14592 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:07:51.345801Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:03:13.269273Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-10T22:15:51.230536Z

Reference resolution

49 of 49 outbound references displayed

verified exact1
verified fuzzy42
unresolved5
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f4e3af0e-826a-4868-a442-9765753e023e · outbound

This paper cites Emerging trends in autonomous vehicle perception: Multi- modal fusion for 3d object detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Emerging trends in autonomous vehicle perception: Multi- modal fusion for 3d object detection

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.724105Z

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 f66e272d-01c2-4d90-b2b5-b2c745ee9268 · outbound

This paper cites Transfusion: Robust lidar-camera fusion for 3d object detection with transformers.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Transfusion: Robust lidar-camera fusion for 3d object detection with transformers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.716023Z

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 87f5dbb5-d53f-4f6c-8f08-48749cbd314e · outbound

This paper cites Mvtec ad — a comprehensive real-world dataset for unsupervised anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Mvtec ad — a comprehensive real-world dataset for unsupervised anomaly detection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.708753Z

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 db599684-029b-4126-a42b-13ecc940a01d · outbound

This paper cites Beyond dents and scratches: Logical constraints in unsupervised anomaly detection and localization.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Beyond dents and scratches: Logical constraints in unsupervised anomaly detection and localization

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.700833Z

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 ae0a9adb-87bb-490c-8957-b7c6e2945030 · outbound

This paper cites The mvtec 3d-ad dataset for unsupervised 3d anomaly detec- tion and localization.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties The mvtec 3d-ad dataset for unsupervised 3d anomaly detec- tion and localization

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.694152Z

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 56cac758-31ae-4e7f-a6fc-44c407f82bfc · outbound

This paper cites The eyecandies dataset for unsupervised multimodal anomaly detection and localization.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties The eyecandies dataset for unsupervised multimodal anomaly detection and localization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.687155Z

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 ead6e644-61de-4da5-9e24-cca972cc9902 · outbound

This paper cites Comple- mentary pseudo multimodal feature for point cloud anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Comple- mentary pseudo multimodal feature for point cloud anomaly detection

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.680085Z

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 25100388-7f90-4add-bbb5-f23867fb6122 · outbound

This paper cites A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties A Survey on Visual Anomaly Detection: Challenge, Approach, and Prospect

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T12:07:51.236255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd64bf12-0488-4d01-bff7-ac22d699e90a · outbound

This paper cites Deformable feature aggregation for dynamic multi-modal 3d object detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Deformable feature aggregation for dynamic multi-modal 3d object detection

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.671834Z

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 202b857d-a730-480e-ae08-e647faa6c199 · outbound

This paper cites Cflow- ad: Real-time unsupervised anomaly detection with localiza- tion via conditional normalizing flows.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Cflow- ad: Real-time unsupervised anomaly detection with localiza- tion via conditional normalizing flows

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.664874Z

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 eb54ed9d-c73b-4a12-b238-09c9e84f0667 · outbound

This paper cites Back to the feature: Clas- sical 3d features are (almost) all you need for 3d anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Back to the feature: Clas- sical 3d features are (almost) all you need for 3d anomaly detection

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.658090Z

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 d527a0de-391d-4982-b4da-c22843ad18ab · outbound

This paper cites Epnet: Enhancing point features with image semantics for 3d object detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Epnet: Enhancing point features with image semantics for 3d object detection

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.651316Z

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 74150920-47a7-4eec-b1ce-8ff1f66dd27c · outbound

This paper cites Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Deep learning-based defect detection of metal parts: evaluating current methods in complex conditions

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.644701Z

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 59dd1c5e-2681-4bb0-a692-811e83ed1bcd · outbound

This paper cites Cfa: Coupled-hypersphere-based feature adaptation for target- oriented anomaly localization.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Cfa: Coupled-hypersphere-based feature adaptation for target- oriented anomaly localization

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.637246Z

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 3d73880a-84ac-4439-b0d0-7adbd9a0a09c · outbound

This paper cites Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T12:07:51.255617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6f2e38c-8cb6-45bf-825c-f351436ee5f5 · outbound

This paper cites Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Deepfusion: Lidar-camera deep fusion for multi-modal 3d object detection

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.627868Z

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 fdfff327-c984-48e4-a5c6-399e8f1f2b24 · outbound

This paper cites Real3d-ad: A dataset of point cloud anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Real3d-ad: A dataset of point cloud anomaly detection

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.620222Z

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 81d6a519-8402-439d-a1e2-94bc968e8207 · outbound

This paper cites Real3d- ad: A dataset of point cloud anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Real3d- ad: A dataset of point cloud anomaly detection

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.612360Z

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 3a780469-2f13-49c1-9346-14aa04c29a8e · outbound

This paper cites Deep industrial image anomaly detection: A survey.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Deep industrial image anomaly detection: A survey

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.605158Z

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 b19798ae-b880-4040-bd5f-4ee58a7a550a · outbound

This paper cites Simplenet: A simple network for image anomaly detection and localization.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Simplenet: A simple network for image anomaly detection and localization

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.597058Z

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 92a9a209-24b8-43f0-974f-898584ab2d9e · outbound

This paper cites Gdxray: The database of x-ray images for nonde- structive testing.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Gdxray: The database of x-ray images for nonde- structive testing

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.589680Z

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 d2dcae94-2892-45d7-a447-db60b1bd71ab · outbound

This paper cites Vt-adl: A vision trans- former network for image anomaly detection and localization.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Vt-adl: A vision trans- former network for image anomaly detection and localization

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.582367Z

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 87e1342d-8475-46a2-a5d4-ab9c6fb66a20 · outbound

This paper cites Radar voxel fusion for 3d object detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Radar voxel fusion for 3d object detection

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.573774Z

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 634b4f46-a689-4d15-97be-2f27e2ff2c67 · outbound

This paper cites Clocs: Camera- lidar object candidates fusion for 3d object detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Clocs: Camera- lidar object candidates fusion for 3d object detection

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.565814Z

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 f561916e-9fb5-4794-8ba8-82c0865f216c · outbound

This paper cites Masked autoencoders for point cloud self-supervised learning.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Masked autoencoders for point cloud self-supervised learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T12:07:51.281511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ef68566-f7ac-486b-ad83-0ab10d255b45 · outbound

This paper cites Towards to- tal recall in industrial anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Towards to- tal recall in industrial anomaly detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.553853Z

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 4ae10b9c-47dd-4ca4-86f1-8ea296daf061 · outbound

This paper cites Towards total re- call in industrial anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Towards total re- call in industrial anomaly detection

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.546292Z

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 c7f390e6-03a2-4eab-923d-223c06d42df7 · outbound

This paper cites Pvel-ad: A large- scale open-world dataset for photovoltaic cell anomaly de- tection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Pvel-ad: A large- scale open-world dataset for photovoltaic cell anomaly de- tection

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.539318Z

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 50decb37-02c1-44cf-b201-e3ec32cce6aa · outbound

This paper cites Duong, Chanh D.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Duong, Chanh D

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.531974Z

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 abc611a0-a89e-4837-befe-b97e399dfdd8 · outbound

This paper cites Lang, Bassam Helou, and Oscar Bei- jbom.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Lang, Bassam Helou, and Oscar Bei- jbom

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.524213Z

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 84523f0c-7c7b-4bb7-8953-0db7d120d701 · outbound

This paper cites Pointaugmenting: Cross-modal augmentation for 3d object detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Pointaugmenting: Cross-modal augmentation for 3d object detection

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.516698Z

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 3cd32bfa-96c3-41ad-bbc9-add0d12c5ce2 · outbound

This paper cites Real-iad: A real-world multi-view dataset for benchmarking versatile industrial anomaly detection,.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Real-iad: A real-world multi-view dataset for benchmarking versatile industrial anomaly detection,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T12:07:51.300213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e3d16ab-9948-44c1-89d7-c17d486fb70b · outbound

This paper cites Multimodal industrial anomaly detection via hybrid fusion.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Multimodal industrial anomaly detection via hybrid fusion

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.505031Z

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 197a4538-a987-4789-ae5f-80596fcadc7d · outbound

This paper cites Multimodal industrial anomaly detection via hybrid fusion.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Multimodal industrial anomaly detection via hybrid fusion

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.498459Z

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 8c6a80a5-8f25-40bf-98c7-e2cf21f9577b · outbound

This paper cites Learning Shared RGB-D Fields: Unified Self-supervised Pre-training for Label-efficient LiDAR-Camera 3D Perception.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Learning Shared RGB-D Fields: Unified Self-supervised Pre-training for Label-efficient LiDAR-Camera 3D Perception

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:07:51.377832Z

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 e74d90c8-4b40-494c-a2ab-c9ffe7b69623 · outbound

This paper cites Deepinteraction: 3d object detection via modal- ity interaction.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Deepinteraction: 3d object detection via modal- ity interaction

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.491955Z

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 c7ab7fa9-c21b-4b19-b513-9ac51a4acd46 · outbound

This paper cites Multi- modal virtual point 3d detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Multi- modal virtual point 3d detection

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.484833Z

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 c377a989-7506-4901-88c1-8c8a2d1bb9b1 · outbound

This paper cites Draem - a discriminatively trained reconstruction embedding for sur- face anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Draem - a discriminatively trained reconstruction embedding for sur- face anomaly detection

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.477428Z

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 63db907e-77cf-47d1-8456-3a9ebe48c3f7 · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T12:07:51.319488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21051e28-ebdb-4c86-afbb-38be2e65d848 · outbound

This paper cites Learning feature inversion for multi-class anomaly de- tection under general-purpose coco-ad benchmark, 2024.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Learning feature inversion for multi-class anomaly de- tection under general-purpose coco-ad benchmark, 2024

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.469440Z

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 04815a5b-fd83-4993-90e2-02f8337b8fbd · outbound

This paper cites Destseg: Segmentation guided denoising student-teacher for anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Destseg: Segmentation guided denoising student-teacher for anomaly detection

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.461760Z

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 84adeada-23aa-479c-95ae-32ad1c833181 · outbound

This paper cites Logicode: An llm-driven framework for logical anomaly detection.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Logicode: An llm-driven framework for logical anomaly detection

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.453616Z

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 6209a9fb-2d63-4206-8786-12116759b21a · outbound

This paper cites Rangelvdet: Boosting 3d object detection in lidar with range image and rgb image.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Rangelvdet: Boosting 3d object detection in lidar with range image and rgb image

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.444667Z

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 5d721a5d-16ea-4eac-aadb-4e9450fa6f29 · outbound

This paper cites Pad: A dataset and benchmark for pose-agnostic anomaly detection, 2023.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Pad: A dataset and benchmark for pose-agnostic anomaly detection, 2023

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.437271Z

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 894dc00a-73a8-4874-b1b8-af64494c6906 · outbound

This paper cites Spot-the-difference self-supervised pre- training for anomaly detection and segmentation, 2022.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Spot-the-difference self-supervised pre- training for anomaly detection and segmentation, 2022

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.428500Z

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 e60fd2a5-c97b-46a1-b3b2-513638c34cc6 · outbound

This paper cites Objects with higher density and larger volume generally require a longer duration.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Objects with higher density and larger volume generally require a longer duration

Reference 46

Resolution: malformed identifier; raw_fallback, observed 2026-08-11T12:07:51.421289Z

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 6a556e24-2c65-40ee-aad3-81c8e1e8f17e · outbound

This paper cites To provide a more intuitive view of our dataset, below are additional dataset samples.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties To provide a more intuitive view of our dataset, below are additional dataset samples

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.412180Z

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 43781d8b-8f03-44b9-875f-dc4ffdc3dd33 · outbound

This paper cites For RGB/Infrared feature extraction, we use the ViT-B/8 model, which is pretrained on ImageNet with DINO.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties For RGB/Infrared feature extraction, we use the ViT-B/8 model, which is pretrained on ImageNet with DINO

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.404909Z

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 d851c56d-57bf-4b55-87c1-8d48bdc31cfe · outbound

This paper cites Here we show the Single 3D Bench- mark, including object-level Auroc in Table 8, point-level Auroc in Table 9.

Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties Here we show the Single 3D Bench- mark, including object-level Auroc in Table 8, point-level Auroc in Table 9

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:07:51.397471Z

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.

Pith citing papers

Observation da3830a8-4bc2-4f47-9968-d2d8679b5a57 · inbound

Visual Anomaly Detection under Complex View-Illumination Interplay: A Large-Scale Benchmark cites this paper.

Visual Anomaly Detection under Complex View-Illumination Interplay: A Large-Scale Benchmark Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T21:03:13.269273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17198b25-558c-4dcc-9454-a04014a505b7 · inbound

Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects cites this paper.

Towards High-Resolution 3D Anomaly Detection: A Scalable Dataset and Real-Time Framework for Subtle Industrial Defects Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T18:47:28.792177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f23b2f8e-6b1a-4aa1-add2-ddfb3e85bbc0 · inbound

Synthesis4AD: Synthetic Anomalies are All You Need for 3D Anomaly Detection cites this paper.

Synthesis4AD: Synthetic Anomalies are All You Need for 3D Anomaly Detection Multi-Sensor Object Anomaly Detection: Unifying Appearance, Geometry, and Internal Properties

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:15:51.234001Z

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.