Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T13:56:33.382609Z
Paper Citation Record · LEDGER
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking
As of 10 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2507.19908.
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 2026-08-10T06:31:04.303077+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 exact3
- verified fuzzy51
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation d72ef24f-7a2b-4ab1-9c21-5c2307709d93 · outbound
This paper cites nuscenes: A multi- modal dataset for autonomous driving.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking nuscenes: A multi- modal dataset for autonomous driving
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:42.297764Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation b24f4778-4da6-44bf-ba61-fdd87d671f72 · outbound
This paper cites ShapeNet: An Information-Rich 3D Model Repository.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking ShapeNet: An Information-Rich 3D Model Repository
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:56:31.545612Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation febaea86-d2ab-460e-aeb1-5bb13598f651 · outbound
This paper cites Joint classification and regression for visual tracking with fully convolutional siamese networks.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Joint classification and regression for visual tracking with fully convolutional siamese networks
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:42.139752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 969c7058-5dae-4091-bdcb-762a84a196aa · outbound
This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Scannet: Richly-annotated 3d reconstructions of indoor scenes
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:41.978595Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation a2d0b9a5-a9cb-48fa-9dcc-89fd9970cacb · outbound
This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Bert: Pre-training of deep bidirectional trans- formers for language understanding
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:56:31.557547Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a5f7272-f11c-4855-ac57-797ada250f6c · outbound
This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking An image is worth 16x16 words: Trans- formers for image recognition at scale
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:41.816799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 587e65c7-d84e-4988-8704-06be6757db90 · outbound
This paper cites 3d-siamrpn: An end-to-end learning method for real-time 3d single object tracking using raw point cloud.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking 3d-siamrpn: An end-to-end learning method for real-time 3d single object tracking using raw point cloud
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:41.684779Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 5b1d91b1-9982-4e84-9702-900d907448db · outbound
This paper cites CLIP-Adapter: Better Vision-Language Models with Feature Adapters.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking CLIP-Adapter: Better Vision-Language Models with Feature Adapters
Reference 8
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8454964d-d7c0-4491-93fc-6f3d673afae0 · outbound
This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Are we ready for autonomous driving? the kitti vision benchmark suite
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:41.503683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 97836163-8ee4-435a-a32d-3857002932c9 · outbound
This paper cites Lever- aging shape completion for 3d siamese tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Lever- aging shape completion for 3d siamese tracking
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:41.333487Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 5fbee345-be9a-4bde-8059-e5241da8b6be · outbound
This paper cites Parameter-efficient transfer learning for nlp.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Parameter-efficient transfer learning for nlp
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:41.129194Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation b6c62bb7-729a-4a04-ac78-7f41552fda06 · outbound
This paper cites Lora: Low-rank adaptation of large language models.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Lora: Low-rank adaptation of large language models
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:56:31.582832Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e57feda-e6da-4813-a7f1-a585260fb4a9 · outbound
This paper cites Clip2point: Transfer clip to point cloud classifica- tion with image-depth pre-training.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Clip2point: Transfer clip to point cloud classifica- tion with image-depth pre-training
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:40.981464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 8a47b0b6-4beb-4693-add0-027896d6fb8c · outbound
This paper cites 3d siamese voxel-to-bev tracker for sparse point clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking 3d siamese voxel-to-bev tracker for sparse point clouds
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:40.839793Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 9cfcc572-51cf-464a-af86-d222f23aaf44 · outbound
This paper cites 3d siamese transformer network for single object tracking on point clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking 3d siamese transformer network for single object tracking on point clouds
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:40.734898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation c43aa39f-11d9-4780-b4a7-55158b5d7ff6 · outbound
This paper cites Vi- sual prompt tuning.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Vi- sual prompt tuning
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:40.561198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 63372031-4381-474d-ba01-40a71ad31a47 · outbound
This paper cites Maple: Multi-modal prompt learning.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Maple: Multi-modal prompt learning
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:40.435504Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation f94e9d99-298f-4f66-97f5-9c22a12d7ec2 · outbound
This paper cites Temporal-aware siamese tracker: Integrate temporal context for 3d object tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Temporal-aware siamese tracker: Integrate temporal context for 3d object tracking
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:40.307539Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 36a211f7-866d-43b0-85d4-646556000e84 · outbound
This paper cites Citetracker: Correlating image and text for visual tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Citetracker: Correlating image and text for visual tracking
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:40.193284Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 9b6ec41a-22f1-4b9b-b667-78cf1dab68ea · outbound
This paper cites Seq- track3d: Exploring sequence information for robust 3d point cloud tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Seq- track3d: Exploring sequence information for robust 3d point cloud tracking
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:40.082273Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d0406810-c8dc-424f-8795-fe3e620284cb · outbound
This paper cites Visual instruction tuning.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Visual instruction tuning
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:39.970666Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 12350588-e199-4356-9309-e42a53a4c9e1 · outbound
This paper cites M3sot: multi-frame, multi- field, multi-space 3d single object tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking M3sot: multi-frame, multi- field, multi-space 3d single object tracking
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:39.774335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 90ed459f-1d6e-49ec-a23a-e88570b0ed02 · outbound
This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking RoBERTa: A Robustly Optimized BERT Pretraining Approach
Reference 23
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d67b48f0-65ce-40e8-8c70-10f08fe693b0 · outbound
This paper cites V oxeltrack: Exploring multi-level voxel representation for 3d point cloud object tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking V oxeltrack: Exploring multi-level voxel representation for 3d point cloud object tracking
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:39.549018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 1f539faa-cc48-40ed-b7aa-49314e93a6f7 · outbound
This paper cites Modeling con- tinuous motion for 3d point cloud object tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Modeling con- tinuous motion for 3d point cloud object tracking
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:39.311946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation de807e23-8206-48cb-adc2-4f85127e10e1 · outbound
This paper cites Exploring point-bev fusion for 3d point cloud ob- ject tracking with transformer.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Exploring point-bev fusion for 3d point cloud ob- ject tracking with transformer
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:39.042867Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation f7a3a29b-956d-4a53-a8be-b245e6a49e6d · outbound
This paper cites Synchronize feature extracting and matching: A single branch framework for 3d object tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Synchronize feature extracting and matching: A single branch framework for 3d object tracking
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:38.848877Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e2bfbe87-1483-4e8b-a8a4-3a1d38793817 · outbound
This paper cites Osp2b: One-stage point-to-box net- work for 3d siamese tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Osp2b: One-stage point-to-box net- work for 3d siamese tracking
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:38.612626Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 552b2d3f-4f57-4627-ad07-19bf220ea85c · outbound
This paper cites Glt-t: Global-local transformer voting for 3d single object tracking in point clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Glt-t: Global-local transformer voting for 3d single object tracking in point clouds
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:38.425473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e27c513a-f0f9-4735-a037-7ab31afa0fd4 · outbound
This paper cites Towards Category Unification of 3D Single Object Tracking on Point Clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Towards Category Unification of 3D Single Object Tracking on Point Clouds
Reference 30
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T13:56:34.015675Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d225956c-ec66-4b29-80ad-f59b7ecaf067 · outbound
This paper cites P2P: Part-to-Part Motion Cues Guide a Strong Tracking Framework for LiDAR Point Clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking P2P: Part-to-Part Motion Cues Guide a Strong Tracking Framework for LiDAR Point Clouds
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T13:56:33.868900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 89db613e-c5bb-4ec1-87f9-4bc15f29869c · outbound
This paper cites St-adapter: Parameter-efficient image-to-video transfer learning.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking St-adapter: Parameter-efficient image-to-video transfer learning
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:38.258863Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e79f93d1-338b-4da0-84ad-1d9c78e7b258 · outbound
This paper cites Masked autoencoders for point cloud self-supervised learning.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Masked autoencoders for point cloud self-supervised learning
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:38.109964Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation c32d41ca-d0a6-4b3e-a198-cf609fb0a5ea · outbound
This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Pointnet: Deep learning on point sets for 3d classification and segmentation
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:56:31.740431Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3ba968a-7607-4933-8b7b-ee6acce2c0b5 · outbound
This paper cites Deep hough voting for 3d object detection in point clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Deep hough voting for 3d object detection in point clouds
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:37.935576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 1513e9d5-c94a-4d49-8c9d-e0da35ce6f4b · outbound
This paper cites P2b: Point-to-box network for 3d object tracking in point clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking P2b: Point-to-box network for 3d object tracking in point clouds
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:37.775506Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 19bbe229-cff3-45f3-a1a6-6d47c423ff53 · outbound
This paper cites Contrast with reconstruct: Contrastive 3d representation learning guided by generative pretraining.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Contrast with reconstruct: Contrastive 3d representation learning guided by generative pretraining
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:37.614844Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 93a8af8b-e6e8-4950-820a-417930847b90 · outbound
This paper cites Learning transferable visual models from natural language supervision.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Learning transferable visual models from natural language supervision
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:37.460460Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d11ae026-8a21-4e77-be75-721474429847 · outbound
This paper cites Ptt: Point-track-transformer module for 3d single object tracking in point clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Ptt: Point-track-transformer module for 3d single object tracking in point clouds
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:37.288217Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 930e8e08-b6e3-4eb1-bcfc-f071fcb46009 · outbound
This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:56:31.813760Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 21c691a3-112e-43a2-a23c-3ec029f46a0e · outbound
This paper cites Scalability in perception for autonomous driving: Waymo open dataset.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Scalability in perception for autonomous driving: Waymo open dataset
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:56:31.828206Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b28d8a60-3066-456d-ad60-463fb3446b80 · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking LLaMA: Open and Efficient Foundation Language Models
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:56:31.843748Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00553f43-b2e5-41c3-a992-12797b607d73 · outbound
This paper cites Correlation pyramid network for 3d single ob- ject tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Correlation pyramid network for 3d single ob- ject tracking
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:37.173335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 819b2707-a359-4471-9361-5141f5cba1f1 · outbound
This paper cites Actionclip: Adapting language-image pretrained models for video action recognition.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Actionclip: Adapting language-image pretrained models for video action recognition
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:37.012684Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e9d39a8f-928c-4949-917a-ec213928a1a2 · outbound
This paper cites M2-clip: A multimodal, multi-task adapting framework for video action recognition.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking M2-clip: A multimodal, multi-task adapting framework for video action recognition
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:36.836936Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 16cbe66e-6d49-4a32-b5b5-dec72ab1979b · outbound
This paper cites Dynamic graph cnn for learning on point clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Dynamic graph cnn for learning on point clouds
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:36.682972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 81781aed-a55b-4271-80af-10387108ba6e · outbound
This paper cites Vita-clip: Video and text adaptive clip via multimodal prompting.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Vita-clip: Video and text adaptive clip via multimodal prompting
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:36.510522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2df80ed3-345d-4152-b82a-42d7a4992cba · outbound
This paper cites Boosting 3d single object tracking with 2d matching distilla- tion and 3d pre-training.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Boosting 3d single object tracking with 2d matching distilla- tion and 3d pre-training
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:36.370120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation d51db03b-1032-48fe-b8c2-1190e1185fe8 · outbound
This paper cites Pointcontrast: Unsupervised pre- training for 3d point cloud understanding.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Pointcontrast: Unsupervised pre- training for 3d point cloud understanding
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:36.266139Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e58d9aa5-d45b-4c0e-91e9-f2282ed97d35 · outbound
This paper cites Cxtrack: Improving 3d point cloud tracking with contextual information.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Cxtrack: Improving 3d point cloud tracking with contextual information
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:36.079042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation ee3de25b-7e3c-4261-84c1-2651117b93a9 · outbound
This paper cites Mbptrack: Improving 3d point cloud tracking with memory networks and box priors.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Mbptrack: Improving 3d point cloud tracking with memory networks and box priors
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:35.935765Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation c35e99c3-6d55-4f64-a017-b5183b17642c · outbound
This paper cites SiamMo: Siamese Motion-Centric 3D Object Tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking SiamMo: Siamese Motion-Centric 3D Object Tracking
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T13:56:33.679201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 835ff202-a65a-4e32-82bb-e75c9f444942 · outbound
This paper cites Joint feature learning and relation modeling for tracking: A one-stream framework.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Joint feature learning and relation modeling for tracking: A one-stream framework
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:35.779583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 266cac8f-0521-4875-9c53-ceb6067d1af5 · outbound
This paper cites Point-bert: Pre-training 3d point cloud transformers with masked point modeling.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Point-bert: Pre-training 3d point cloud transformers with masked point modeling
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:35.623718Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation be2fca86-63dd-4775-b02f-7aa809f34786 · outbound
This paper cites Instance-aware dynamic prompt tuning for pre-trained point cloud models.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Instance-aware dynamic prompt tuning for pre-trained point cloud models
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:35.468482Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2fbea7e5-6dc8-49f8-90ec-199bf5949909 · outbound
This paper cites Robust 3d tracking with quality-aware shape completion.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Robust 3d tracking with quality-aware shape completion
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:35.321656Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 10e830ff-1b4f-4dfa-8abf-d5aa7db31531 · outbound
This paper cites Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:56:32.818393Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a5cf4468-0c26-4a72-8d36-23cb2fa10f13 · outbound
This paper cites Pointclip: Point cloud understanding by clip.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Pointclip: Point cloud understanding by clip
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:35.173477Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2dbcc65a-4348-4b31-9828-843e3890f9e9 · outbound
This paper cites Box-aware feature en- hancement for single object tracking on point clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Box-aware feature en- hancement for single object tracking on point clouds
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:35.040892Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 28e17a64-3c71-4cd8-ba54-03ced89d2103 · outbound
This paper cites Beyond 3d siamese tracking: A motion-centric paradigm for 3d single object tracking in point clouds.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Beyond 3d siamese tracking: A motion-centric paradigm for 3d single object tracking in point clouds
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:34.890149Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation f45a1654-3266-41bf-8ea5-f030eb1e28c3 · outbound
This paper cites Odtrack: Online dense temporal token learning for visual tracking.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Odtrack: Online dense temporal token learning for visual tracking
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:34.778005Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 857194c5-f124-48ae-b1d1-5de614899427 · outbound
This paper cites Pttr: Relational 3d point cloud object tracking with transformer.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Pttr: Relational 3d point cloud object tracking with transformer
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:34.604003Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation ee6c56b4-16af-4f85-bbbc-db75cdb483ee · outbound
This paper cites Learning to prompt for vision-language models.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Learning to prompt for vision-language models
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:34.397250Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 94b194a9-7157-4c0f-832c-2734366993de · outbound
This paper cites Dynamic adapter meets prompt tuning: Parameter-efficient transfer learning for point cloud analysis.
TrackAny3D: Transferring Pretrained 3D Models for Category-unified 3D Point Cloud Tracking Dynamic adapter meets prompt tuning: Parameter-efficient transfer learning for point cloud analysis
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T13:56:34.190919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Pith citing papers
No inbound Pith citation observations are available.