Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:28:15.940386Z
Paper Citation Record · LEDGER
SAM4D: Segment Anything in Camera and LiDAR Streams
As of 19 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2506.21547.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
64 of 64 outbound references displayed
- verified exact2
- verified fuzzy48
- unresolved14
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 2ac381a2-7a67-4441-b1a1-e7c66b4d829c · outbound
This paper cites LangOcc: Self-Supervised Open Vocabulary Occupancy Estimation via Volume Rendering.
SAM4D: Segment Anything in Camera and LiDAR Streams LangOcc: Self-Supervised Open Vocabulary Occupancy Estimation via Volume Rendering
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:10.803060Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9992915a-c8e1-4f4f-80ae-be853b1b3b11 · outbound
This paper cites Window Attention is Bugged: How not to Interpolate Position Embeddings.
SAM4D: Segment Anything in Camera and LiDAR Streams Window Attention is Bugged: How not to Interpolate Position Embeddings
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T22:28:16.533009Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 89010207-a54a-4a6e-8e9f-974003b12214 · outbound
This paper cites nuscenes: A multi- modal dataset for autonomous driving.
SAM4D: Segment Anything in Camera and LiDAR Streams nuscenes: A multi- modal dataset for autonomous driving
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:29:27.387049Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6b49c0f9-68f1-4c6e-a557-29ab62811d22 · outbound
This paper cites Mopa: Multi-modal prior aided do- main adaptation for 3d semantic segmentation.
SAM4D: Segment Anything in Camera and LiDAR Streams Mopa: Multi-modal prior aided do- main adaptation for 3d semantic segmentation
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:29:27.346250Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ad728328-d395-4920-9852-d916c8ae3c76 · outbound
This paper cites Rsprompter: Learning to prompt for remote sensing instance segmenta- tion based on visual foundation model.
SAM4D: Segment Anything in Camera and LiDAR Streams Rsprompter: Learning to prompt for remote sensing instance segmenta- tion based on visual foundation model
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:29:27.303638Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c7c4142c-3c5d-44b1-85b9-54f9f2588850 · outbound
This paper cites Clip2scene: Towards label-efficient 3d scene under- standing by clip.
SAM4D: Segment Anything in Camera and LiDAR Streams Clip2scene: Towards label-efficient 3d scene under- standing by clip
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:29:27.262150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation bce75e2d-29a5-48c6-990d-9a8cdbddb7e4 · outbound
This paper cites SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More.
SAM4D: Segment Anything in Camera and LiDAR Streams SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:11.282044Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a57b0d19-3363-47fc-9907-32a96d8e68d4 · outbound
This paper cites Futr3d: A unified sensor fusion framework for 3d detection.
SAM4D: Segment Anything in Camera and LiDAR Streams Futr3d: A unified sensor fusion framework for 3d detection
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:29:27.192187Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6ff831bb-075d-4614-baa4-f0b6d2a39902 · outbound
This paper cites Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion.
SAM4D: Segment Anything in Camera and LiDAR Streams Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:29:27.149445Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 05c13c22-e3f8-4399-8f0e-f50900c6da1c · outbound
This paper cites 4d spatio-temporal convnets: Minkowski convolutional neural networks.
SAM4D: Segment Anything in Camera and LiDAR Streams 4d spatio-temporal convnets: Minkowski convolutional neural networks
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:29:26.651484Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e682c806-5e8d-44e4-a89b-2d054e40b149 · outbound
This paper cites Benchmarking robustness of 3d object detection to common corruptions.
SAM4D: Segment Anything in Camera and LiDAR Streams Benchmarking robustness of 3d object detection to common corruptions
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:25.874669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5a5a5369-4943-489d-95df-0dedf5477d85 · outbound
This paper cites Interactive4D: Interactive 4D LiDAR Segmentation.
SAM4D: Segment Anything in Camera and LiDAR Streams Interactive4D: Interactive 4D LiDAR Segmentation
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T22:28:16.308866Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 288c131c-5716-4678-a671-72ffd04b7912 · outbound
This paper cites Scale dispar- ity of instances in interactive point cloud segmentation.
SAM4D: Segment Anything in Camera and LiDAR Streams Scale dispar- ity of instances in interactive point cloud segmentation
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:25.321476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c4d0897f-45dc-4955-89aa-92352ea36eb2 · outbound
This paper cites Deep residual learning for image recognition.
SAM4D: Segment Anything in Camera and LiDAR Streams Deep residual learning for image recognition
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:24.915851Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 9ab79ba9-7ea9-4821-bdde-d809574fc80a · outbound
This paper cites Segment3d: Learning fine-grained class-agnostic 3d segmentation without manual labels.
SAM4D: Segment Anything in Camera and LiDAR Streams Segment3d: Learning fine-grained class-agnostic 3d segmentation without manual labels
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:24.417648Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0eb6b550-77ab-43e2-bacb-b39043093dc1 · outbound
This paper cites Segment anything in high qual- ity.
SAM4D: Segment Anything in Camera and LiDAR Streams Segment anything in high qual- ity
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:24.209914Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 27d59497-94e5-47ee-b449-e591fd5d1db1 · outbound
This paper cites Segment any- thing.
SAM4D: Segment Anything in Camera and LiDAR Streams Segment any- thing
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:24.021950Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b48e889b-3f05-4a1d-9e35-34e7b5d7afaa · outbound
This paper cites Mseg3d: Multi-modal 3d semantic segmentation for autonomous driv- ing.
SAM4D: Segment Anything in Camera and LiDAR Streams Mseg3d: Multi-modal 3d semantic segmentation for autonomous driv- ing
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:23.828327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8e8cfae4-d57b-4452-a94a-dc2bc45c40b2 · outbound
This paper cites Pmafusion: Projection-based multi-modal alignment for 3d semantic oc- cupancy prediction.
SAM4D: Segment Anything in Camera and LiDAR Streams Pmafusion: Projection-based multi-modal alignment for 3d semantic oc- cupancy prediction
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:23.627826Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 57ba217e-c2f3-4515-9b7b-d9f9deebdb50 · outbound
This paper cites Lwsis: Lidar-guided weakly super- vised instance segmentation for autonomous driving.
SAM4D: Segment Anything in Camera and LiDAR Streams Lwsis: Lidar-guided weakly super- vised instance segmentation for autonomous driving
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:23.454887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 4852bd04-6014-4ed3-b718-1fabca8ccc35 · outbound
This paper cites Unifying voxel-based representation with transformer for 3d object detection.
SAM4D: Segment Anything in Camera and LiDAR Streams Unifying voxel-based representation with transformer for 3d object detection
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:12.516765Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3ad836e0-5447-4f84-8b78-4f13a6c2c4b3 · outbound
This paper cites Bevfusion: A simple and robust lidar-camera fusion framework.
SAM4D: Segment Anything in Camera and LiDAR Streams Bevfusion: A simple and robust lidar-camera fusion framework
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:12.613265Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7dc72b01-e2f8-486a-93c7-5cb8c9a9fc75 · outbound
This paper cites Vlm2scene: Self-supervised image-text-lidar learning with foundation models for autonomous driving scene understanding.
SAM4D: Segment Anything in Camera and LiDAR Streams Vlm2scene: Self-supervised image-text-lidar learning with foundation models for autonomous driving scene understanding
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:23.274589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 69cefcba-e25b-4313-924f-7d8e5fdfcbb3 · outbound
This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection.
SAM4D: Segment Anything in Camera and LiDAR Streams Grounding dino: Marrying dino with grounded pre-training for open-set object detection
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:23.136403Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 521ff32b-f73d-4f80-be6f-405ce9ac529f · outbound
This paper cites Segment any point cloud sequences by distilling vision foundation models.
SAM4D: Segment Anything in Camera and LiDAR Streams Segment any point cloud sequences by distilling vision foundation models
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:22.999539Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 887d42bc-bd97-46b5-a0d5-ea8e716bc9d5 · outbound
This paper cites Bevfusion: Multi- task multi-sensor fusion with unified bird’s-eye view repre- sentation.
SAM4D: Segment Anything in Camera and LiDAR Streams Bevfusion: Multi- task multi-sensor fusion with unified bird’s-eye view repre- sentation
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:22.716845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1ebe25f0-709a-47bd-bf85-0e8823cd6382 · outbound
This paper cites See more and know more: Zero- shot point cloud segmentation via multi-modal visual data.
SAM4D: Segment Anything in Camera and LiDAR Streams See more and know more: Zero- shot point cloud segmentation via multi-modal visual data
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:22.455639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 58779a7e-db85-41b4-87e4-46f68b9d48f5 · outbound
This paper cites Segment anything in medical images.
SAM4D: Segment Anything in Camera and LiDAR Streams Segment anything in medical images
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:22.248901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 06358cd6-5af7-4a6b-b613-7a4e03d3338e · outbound
This paper cites Segment anything model for medical image analysis: an experimental study.
SAM4D: Segment Anything in Camera and LiDAR Streams Segment anything model for medical image analysis: an experimental study
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:21.961123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c2693f9a-04ae-4461-9ac0-effec3427f74 · outbound
This paper cites Robust 3d semantic segmentation based on multi-phase multi-modal fusion for intelligent vehicles.
SAM4D: Segment Anything in Camera and LiDAR Streams Robust 3d semantic segmentation based on multi-phase multi-modal fusion for intelligent vehicles
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:21.593696Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 7223ce68-41fb-4da4-9e6c-4791ad46c17f · outbound
This paper cites Better call sal: Towards learning to segment anything in lidar.
SAM4D: Segment Anything in Camera and LiDAR Streams Better call sal: Towards learning to segment anything in lidar
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:21.306518Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 00e01074-674a-4b09-88cc-8faa5e1808bc · outbound
This paper cites Co-occ: Coupling explicit feature fusion with volume rendering regularization for multi-modal 3d semantic occupancy prediction.
SAM4D: Segment Anything in Camera and LiDAR Streams Co-occ: Coupling explicit feature fusion with volume rendering regularization for multi-modal 3d semantic occupancy prediction
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:21.155493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 56222498-ccbf-4815-9543-67b0663ff15d · outbound
This paper cites Openscene: 3d scene understanding with open vocabularies.
SAM4D: Segment Anything in Camera and LiDAR Streams Openscene: 3d scene understanding with open vocabularies
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:20.883231Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 3b0fe05a-39b8-48ef-977e-87226489e8e4 · outbound
This paper cites Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d.
SAM4D: Segment Anything in Camera and LiDAR Streams Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:20.604570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 95121827-8a7d-44fc-878e-3baaecc68ddd · outbound
This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.
SAM4D: Segment Anything in Camera and LiDAR Streams The 2017 DAVIS Challenge on Video Object Segmentation
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:13.642128Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3951558-4fb3-44c4-9701-ac99923d386d · outbound
This paper cites Learn- ing transferable visual models from natural language super- vision.
SAM4D: Segment Anything in Camera and LiDAR Streams Learn- ing transferable visual models from natural language super- vision
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:20.358640Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d33ec2b0-c661-4b84-9eeb-16412d686622 · outbound
This paper cites SAM 2: Segment Anything in Images and Videos.
SAM4D: Segment Anything in Camera and LiDAR Streams SAM 2: Segment Anything in Images and Videos
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:13.828639Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ce97f8d-5518-48cb-be0c-b13437d839de · outbound
This paper cites Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection.
SAM4D: Segment Anything in Camera and LiDAR Streams Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:13.888243Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6bb1e929-f93e-46d1-a1c2-f718a3ecead6 · outbound
This paper cites Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks.
SAM4D: Segment Anything in Camera and LiDAR Streams Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:13.937878Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 04eeb661-edeb-4890-abb3-1f31f9b7038a · outbound
This paper cites Hi- era: A hierarchical vision transformer without the bells-and- whistles.
SAM4D: Segment Anything in Camera and LiDAR Streams Hi- era: A hierarchical vision transformer without the bells-and- whistles
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:20.124015Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation fe3c8e16-b962-4f90-a250-866c14332d9d · outbound
This paper cites Mm-tta: multi-modal test-time adaptation for 3d 10 semantic segmentation.
SAM4D: Segment Anything in Camera and LiDAR Streams Mm-tta: multi-modal test-time adaptation for 3d 10 semantic segmentation
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:19.905563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8e8a36f8-76dc-4376-afae-5d73055b4523 · outbound
This paper cites Scalability in perception for autonomous driving: Waymo open dataset.
SAM4D: Segment Anything in Camera and LiDAR Streams Scalability in perception for autonomous driving: Waymo open dataset
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:19.679837Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 10904c99-98c2-4407-80de-7fd0d75e0fb1 · outbound
This paper cites OVO: Open-Vocabulary Occupancy.
SAM4D: Segment Anything in Camera and LiDAR Streams OVO: Open-Vocabulary Occupancy
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:14.311420Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 048dea18-c13c-43bc-889b-9508a4246db2 · outbound
This paper cites TorchSparse: Efficient Point Cloud Inference Engine.
SAM4D: Segment Anything in Camera and LiDAR Streams TorchSparse: Efficient Point Cloud Inference Engine
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:19.394459Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6d4e4b1c-5c4b-42ef-bb94-67dc322153bb · outbound
This paper cites TorchSparse++: Efficient Point Cloud Engine.
SAM4D: Segment Anything in Camera and LiDAR Streams TorchSparse++: Efficient Point Cloud Engine
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:19.142619Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2ca008ae-81d6-454e-b188-3f093be001e1 · outbound
This paper cites Can SAM Segment Anything? When SAM Meets Camouflaged Object Detection.
SAM4D: Segment Anything in Camera and LiDAR Streams Can SAM Segment Anything? When SAM Meets Camouflaged Object Detection
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:14.554591Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd6a4028-5a97-44df-9a51-3348a75155a6 · outbound
This paper cites Vdbfusion: Flexible and efficient tsdf integration of range sensor data.
SAM4D: Segment Anything in Camera and LiDAR Streams Vdbfusion: Flexible and efficient tsdf integration of range sensor data
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:18.889648Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 4514438b-612b-45ce-ad7c-9f0799eaac10 · outbound
This paper cites Pop-3d: Open-vocabulary 3d occupancy prediction from im- ages.
SAM4D: Segment Anything in Camera and LiDAR Streams Pop-3d: Open-vocabulary 3d occupancy prediction from im- ages
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:18.596931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b20dc3c7-d8d9-4ed9-837a-c7e0b4f764b8 · outbound
This paper cites Occgen: Gener- ative multi-modal 3d occupancy prediction for autonomous driving.
SAM4D: Segment Anything in Camera and LiDAR Streams Occgen: Gener- ative multi-modal 3d occupancy prediction for autonomous driving
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:18.397216Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5117500d-1e4f-4828-9c67-3c422536abfc · outbound
This paper cites Meta- rangeseg: Lidar sequence semantic segmentation using mul- tiple feature aggregation.
SAM4D: Segment Anything in Camera and LiDAR Streams Meta- rangeseg: Lidar sequence semantic segmentation using mul- tiple feature aggregation
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:18.304287Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1826d538-8db4-4539-abf5-f4c4d9e65dd5 · outbound
This paper cites Lidar2map: In defense of lidar-based semantic map construction using online camera distillation.
SAM4D: Segment Anything in Camera and LiDAR Streams Lidar2map: In defense of lidar-based semantic map construction using online camera distillation
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:18.142947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2f119ed4-54bf-4b06-a0fc-111514c14e61 · outbound
This paper cites RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions.
SAM4D: Segment Anything in Camera and LiDAR Streams RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:15.020275Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57ac75e5-3316-46cf-b835-ff898c2efd3b · outbound
This paper cites Sparsefusion: Fusing multi-modal sparse representations for multi-sensor 3d object detection.
SAM4D: Segment Anything in Camera and LiDAR Streams Sparsefusion: Fusing multi-modal sparse representations for multi-sensor 3d object detection
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:17.974967Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c45b0873-6ebf-48b1-92e7-f03a01d3cbff · outbound
This paper cites Efficientsam: Leveraged masked image pretraining for efficient segment anything.
SAM4D: Segment Anything in Camera and LiDAR Streams Efficientsam: Leveraged masked image pretraining for efficient segment anything
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:17.828763Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 3af955d8-7007-4b70-ab22-03a92915b5a5 · outbound
This paper cites Cross modal trans- former: Towards fast and robust 3d object detection.
SAM4D: Segment Anything in Camera and LiDAR Streams Cross modal trans- former: Towards fast and robust 3d object detection
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:17.689018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f769896a-2525-4489-91e7-b3235d7d941f · outbound
This paper cites SAM3D: Segment Anything in 3D Scenes.
SAM4D: Segment Anything in Camera and LiDAR Streams SAM3D: Segment Anything in 3D Scenes
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:15.313315Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 92380653-c9af-4de4-89df-45bdfeb533d8 · outbound
This paper cites Clip2: Contrastive language- image-point pretraining from real-world point cloud data.
SAM4D: Segment Anything in Camera and LiDAR Streams Clip2: Contrastive language- image-point pretraining from real-world point cloud data
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:17.517182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6a9bb9de-4862-431d-b96a-c716d17ce480 · outbound
This paper cites Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.
SAM4D: Segment Anything in Camera and LiDAR Streams Faster Segment Anything: Towards Lightweight SAM for Mobile Applications
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:15.468490Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5079f15d-3d6f-4ffa-9eb6-60410e2dbaf9 · outbound
This paper cites Sparselif: High-performance sparse lidar- camera fusion for 3d object detection.
SAM4D: Segment Anything in Camera and LiDAR Streams Sparselif: High-performance sparse lidar- camera fusion for 3d object detection
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:17.344616Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 266c0635-4718-4ac9-812a-679da8aeb5ac · outbound
This paper cites Clip-fo3d: Learning free open-world 3d scene representations from 2d dense clip.
SAM4D: Segment Anything in Camera and LiDAR Streams Clip-fo3d: Learning free open-world 3d scene representations from 2d dense clip
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:17.210553Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8d974c38-1dd3-48e8-9b15-0dbb479abf16 · outbound
This paper cites Fusionocc: Multi-modal fusion for 3d occupancy prediction.
SAM4D: Segment Anything in Camera and LiDAR Streams Fusionocc: Multi-modal fusion for 3d occupancy prediction
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:17.060316Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0f863402-eebc-4571-85b7-2e6511037a3a · outbound
This paper cites Fast Segment Anything.
SAM4D: Segment Anything in Camera and LiDAR Streams Fast Segment Anything
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:28:15.753789Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b7be7dc-94ce-4f9c-8dad-b1f021f0db35 · outbound
This paper cites Veon: V ocabulary- enhanced occupancy prediction.
SAM4D: Segment Anything in Camera and LiDAR Streams Veon: V ocabulary- enhanced occupancy prediction
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:16.897444Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b7d79488-01cb-4ca7-9565-da8cafc064af · outbound
This paper cites Point-SAM: Promptable 3d segmentation model for point clouds.
SAM4D: Segment Anything in Camera and LiDAR Streams Point-SAM: Promptable 3d segmentation model for point clouds
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T22:28:16.708075Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Pith citing papers
No inbound Pith citation observations are available.