Pith. sign in

Paper Citation Record · LEDGER

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection

As of 15 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2505.16029.

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

pith.paper-citation-record.v1
2505.16029 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:12:02.794846Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

47 of 47 outbound references displayed

  • verified exact2
  • verified fuzzy30
  • unresolved15
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 35a7ad7c-f4ab-409c-9510-7a631ae4da72 · outbound

This paper cites End-to-end object detection with transformers,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection End-to-end object detection with transformers,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.598179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.598179Z digest=sha256:e480d7b54c820e559ea067ef528d9c01cad00b16663c44bd7c5fae2aaa4fe821

Observation 5f4ed1cd-3b57-4f92-8d5a-adc8a50eaaaf · outbound

This paper cites An end-to-end transformer model for 3d object detection,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection An end-to-end transformer model for 3d object detection,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.322619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.603364Z digest=sha256:fb69ed620145e851b66f793ecef5468a28b5d7a6f3574aa721c808ed8c0dd6d6

Observation d243019a-2e10-4774-abe5-bf4cfa62e4a7 · outbound

This paper cites Motr: End-to-end multiple-object tracking with transformer,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Motr: End-to-end multiple-object tracking with transformer,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.309845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.607635Z digest=sha256:8d9d617003a63fdc166a97eaeb6c98fdc5dfbb1f5920ab58463669394d545110

Observation 5d15bc1e-c76b-4110-9510-cd7410c37809 · outbound

This paper cites Planning-oriented autonomous driving,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Planning-oriented autonomous driving,

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.611309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.611309Z digest=sha256:ef11ee3e0ec069026b0c8eab24165391b64d1690f8d4fcb8fe0f1837f3101eda

Observation a1ddfb41-29d0-4891-87a4-ca9dbc38be56 · outbound

This paper cites Monodetr: Depth-guided transformer for monocular 3d object detection,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Monodetr: Depth-guided transformer for monocular 3d object detection,

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.615691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.615691Z digest=sha256:56d8308631f3aa875fb503c7333503effa5d2cb2907755bd0e406c2ba67ae30f

Observation 750e374c-2107-4e4c-8351-9782fc45612d · outbound

This paper cites 3dmot- former: Graph transformer for online 3d multi-object tracking,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection 3dmot- former: Graph transformer for online 3d multi-object tracking,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.285937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.619349Z digest=sha256:30c4547691bff30be63c6ee4d8df585a035a2715fe83647584f11ccddb8831ea

Observation 4982b097-8899-45e4-ab4d-8e0a315fba4c · outbound

This paper cites Auto4D: Learning to Label 4D Objects from Sequential Point Clouds.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Auto4D: Learning to Label 4D Objects from Sequential Point Clouds

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:12:02.879469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.623473Z digest=sha256:5e2726e63c3ed0f6a74daa805c7017355a72ae0bdfa93fec0c427cda5f339020

Observation fa1993fc-b584-4ce9-b38e-42e359e3a811 · outbound

This paper cites Once detected, never lost: Surpassing human performance in offline lidar based 3d object detection,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Once detected, never lost: Surpassing human performance in offline lidar based 3d object detection,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.273285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.628514Z digest=sha256:497873a29efd521ec1f317d7f37d405ae534158f59a317ce6168302da9e44784

Observation 9d942f39-202d-4286-96c2-14e03ce8d3ec · outbound

This paper cites Detzero: Rethinking offboard 3d object detection with long-term sequential point clouds,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Detzero: Rethinking offboard 3d object detection with long-term sequential point clouds,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.261596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.633439Z digest=sha256:c70c28b800bc4f457115ae28e6165a2430a276f3f719131caae089619fc36bd9

Observation ef9ef149-8396-4f5d-af1a-c60ba650d190 · outbound

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

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Scalability in perception for autonomous driving: Waymo open dataset,

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.637051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.637051Z digest=sha256:a1ca0ccf48463c138bf70c038c0a1f7b1915edb94f77d1958e6dad5a8960a7f6

Observation 96172834-3a9f-4d6e-a3f1-d0db900c706d · outbound

This paper cites nuscenes: A multimodal dataset for autonomous driving,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection nuscenes: A multimodal dataset for autonomous driving,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.641172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.641172Z digest=sha256:7a8015df57cefb063669c454943bf10db726174c0451ff70406375889a7e2cf1

Observation 7c2bfdaf-245c-42a7-b4e6-c3059c2e6ea8 · outbound

This paper cites The h3d dataset for full-surround 3d multi-object detection and tracking in crowded urban scenes,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection The h3d dataset for full-surround 3d multi-object detection and tracking in crowded urban scenes,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.234902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.644922Z digest=sha256:77d26ab157e72e0986ab97f84c515bf60e8e7c849debeb77bbb3abdc65d4a109

Observation 3b6a5843-30cb-4f33-bc07-a15e75148314 · outbound

This paper cites Stcrowd: A multimodal dataset for pedes- trian perception in crowded scenes,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Stcrowd: A multimodal dataset for pedes- trian perception in crowded scenes,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.220740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.649065Z digest=sha256:deb622f25dc9bae071b581831dfebcbf20b092d1ed4a6dcac228b01f00b3b163

Observation 958ebef6-fba6-4597-b0d4-183f1bb67e4c · outbound

This paper cites Bevfusion: Multi-task multi-sensor fusion with unified bird’s- eye view representation,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Bevfusion: Multi-task multi-sensor fusion with unified bird’s- eye view representation,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.653582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.653582Z digest=sha256:df48d1077dcb5b5e5fa0fe337fc9d9f103790549e27d0168b6d28abe8f8c6543

Observation 9e6fbc79-a620-4729-b089-4305e149fdc4 · outbound

This paper cites Center-based 3d object detec- tion and tracking,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Center-based 3d object detec- tion and tracking,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.200646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.658731Z digest=sha256:85239507fdcd9cdf7e3005ab1e7124449dd1389d151dffd9da563597c406ecd5

Observation d21b307e-accc-4388-ac37-6a5bdca390d2 · outbound

This paper cites 3d multi-object tracking: A baseline and new evaluation metrics,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection 3d multi-object tracking: A baseline and new evaluation metrics,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.188314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.663696Z digest=sha256:b3ae5e9fe5f50211c1c3df7b1fc5f339059785789befa1d16abcfe87c3dd9e6b

Observation 2f01602c-923f-4cf1-bae4-95ae8796de2c · outbound

This paper cites Gnn3dmot: Graph neural network for 3d multi-object tracking with 2d-3d multi-feature learning,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Gnn3dmot: Graph neural network for 3d multi-object tracking with 2d-3d multi-feature learning,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.176715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.667844Z digest=sha256:767a7aea4513003a74969cf60ab9ef11aec40449abd2378cf4f60ec5998a9485

Observation d6baedf9-1182-43be-9919-a06d4e34b3a5 · outbound

This paper cites Exploring simple 3d multi-object tracking for autonomous driving,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Exploring simple 3d multi-object tracking for autonomous driving,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.162884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.671361Z digest=sha256:b8195bb0133e32e629aea66e4ca98c10ae927cb7ce3627db28ba0bf9ad0a81fd

Observation 27bcbb9a-09ed-4276-bf86-d82d5a33e031 · outbound

This paper cites Spot: Spatiotemporal modeling for 3d object tracking,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Spot: Spatiotemporal modeling for 3d object tracking,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.150831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.675978Z digest=sha256:df3904d956ff7772eb99016f1880bb12449be8e227758d9988e08956d8f17991

Observation c227c610-879c-45be-a250-db27e3794082 · outbound

This paper cites Tracking objects as points,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Tracking objects as points,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.138693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.679970Z digest=sha256:cfb557cab3839ccc1b9798983d91a122120daf320ecf4847bf0ccabf36c40326

Observation 0b43a5c4-7ea6-420b-9f30-1a857708aace · outbound

This paper cites Probabilistic 3d multi- modal, multi-object tracking for autonomous driving,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Probabilistic 3d multi- modal, multi-object tracking for autonomous driving,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.126607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.684214Z digest=sha256:5640b62f612120dc968d2c03b403ad9d445e49becfa76f45e9348f634c479b76

Observation 3ab48582-fa9e-40f3-8e42-0da689cad68c · outbound

This paper cites Pedestrian detection in crowded scenes,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Pedestrian detection in crowded scenes,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.114629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.688102Z digest=sha256:374d22cb4642f68e85863362b40cd7e5a8bee8c2dc949a394fb417a69ff1d842

Observation 289d13ba-9d64-47d8-8bcf-12f4f4e1ef01 · outbound

This paper cites How far are we from solving pedestrian detection?.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection How far are we from solving pedestrian detection?

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.102761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.692567Z digest=sha256:e8c2444b66a35f5470d579275c9afd5f4c44046dd891b069883d202e6c1f7a60

Observation c6c81ee0-08fc-49a7-a847-8c5c6926ea2e · outbound

This paper cites Multi-view 3d human tracking in crowded scenes,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Multi-view 3d human tracking in crowded scenes,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.090808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.696910Z digest=sha256:8ccf986417199a099a732acec461fe9905062aaefd92c6cd51e8e2c19cd88fb8

Observation f83ccce6-a419-4d3d-a476-22af46838ed6 · outbound

This paper cites On multi-modal people tracking from mobile platforms in very crowded and dynamic environments,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection On multi-modal people tracking from mobile platforms in very crowded and dynamic environments,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.078823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.701396Z digest=sha256:d597ee9c2d9b866c343577c612b8602c638d16e4cfc22d3bb78d7dff84b3ffc7

Observation 797f2075-cbf7-4946-b28f-90acf1184d9e · outbound

This paper cites Where, what, whether: Multi-modal learning meets pedestrian detection,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Where, what, whether: Multi-modal learning meets pedestrian detection,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.067887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.705986Z digest=sha256:e7b9fa235dcb8e14a74079e56f153cf5e5ff5de86c571f4ecdc5658fd9694ac2

Observation 2aaf0e0d-a8f1-45eb-83fa-de1ff9515784 · outbound

This paper cites Detection in crowded scenes: One proposal, multiple predictions,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Detection in crowded scenes: One proposal, multiple predictions,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.057032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.710457Z digest=sha256:7baad3895b26869a32ee83c653029b58b2193d4847fd0693fe304c0656a3d500

Observation 09ab42ff-a16f-4f2a-b091-aff561fbf8e7 · outbound

This paper cites Temporal- context enhanced detection of heavily occluded pedestrians,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Temporal- context enhanced detection of heavily occluded pedestrians,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.045950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.715040Z digest=sha256:4857d2607549d19b5172c86181e39fe327f15c09ab792a94935735f5d4d0a9e3

Observation edb8c1b8-430a-483a-ae7b-94eade4b5886 · outbound

This paper cites Graininess-aware deep feature learning for robust pedestrian detection,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Graininess-aware deep feature learning for robust pedestrian detection,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.032670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.719097Z digest=sha256:e37ae1545845ba8c36179b27ce06b137c20c2be92a700e52e4f8c6821eb10303

Observation 2c24be1a-f5e9-4e1e-971c-cc0250492db2 · outbound

This paper cites Occlusion handling and multi-scale pedestrian detection based on deep learning: A review,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Occlusion handling and multi-scale pedestrian detection based on deep learning: A review,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.018499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.723305Z digest=sha256:3a939451518e6f18dcf07733457148c0d740a5a093cbe3bcaec0f492258021ec

Observation 153fecbf-e7b9-4850-a644-bc6d37727bfb · outbound

This paper cites Tracking pedestrian heads in dense crowd,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Tracking pedestrian heads in dense crowd,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:03.005672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.726856Z digest=sha256:314b2e28da43e08d51dea4c4698dff36dba31dfc0972aa08898bdaf756121731

Observation 05e40b6e-2003-444c-8ef0-965e17d32695 · outbound

This paper cites Mask-guided attention network for occluded pedestrian detection,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Mask-guided attention network for occluded pedestrian detection,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:02.992579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.731338Z digest=sha256:c358e86b93cc32b4b44e654369aaa9262b6d590e5cf6b4ab5bdc15fafc98e727

Observation 66f80e89-f29f-4755-b761-3b65b9cef147 · outbound

This paper cites Occlusion-aware r- cnn: Detecting pedestrians in a crowd,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Occlusion-aware r- cnn: Detecting pedestrians in a crowd,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:02.979609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.736234Z digest=sha256:c57ca26b7dbd580e10dd343abf719172d14abd63682a448fa491ddfe1d278253

Observation 1359af3c-478e-46a8-b166-4942f3d4b73f · outbound

This paper cites Nms by representative region: Towards crowded pedestrian detection by proposal pairing,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Nms by representative region: Towards crowded pedestrian detection by proposal pairing,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:02.966757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.739757Z digest=sha256:693977ba65b57c0c2e32812a1ee3961ad7b9cbd337dc10b605a66902d1a5927c

Observation 25458775-027a-4574-9e20-f34d8bc0105d · outbound

This paper cites DETR for Crowd Pedestrian Detection.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection DETR for Crowd Pedestrian Detection

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:12:02.862932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.743335Z digest=sha256:dc741aad9c705bf740de4ad192aef6cef3a0bd0066712eb0f15f35ac9e630c26

Observation 8452933f-3cac-438b-95e5-4723aa2b9b16 · outbound

This paper cites CrowdHuman: A Benchmark for Detecting Human in a Crowd.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection CrowdHuman: A Benchmark for Detecting Human in a Crowd

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.747406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.747406Z digest=sha256:fdb66ed48f0a84cda0e3dc1cbb0ee9ed21179d1ac4f8d199bb9f40a5e10d3b0f

Observation 3108ac28-0bed-4691-b38c-ca0897f4274b · outbound

This paper cites Crowdpose: Efficient crowded scenes pose estimation and a new benchmark,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Crowdpose: Efficient crowded scenes pose estimation and a new benchmark,

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.752019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.752019Z digest=sha256:9bf79aaa6df21814d2f6f0f86f4152cb93881bbfca10b549d282c1d457c1c68b

Observation f8c9c3b3-4052-4242-8da4-6fcbfc026bee · outbound

This paper cites MOT20: A benchmark for multi object tracking in crowded scenes.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection MOT20: A benchmark for multi object tracking in crowded scenes

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.755723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.755723Z digest=sha256:9c575e04404404d57c5b27e1472a4e58e6d380f28931e549a8af2f75330da1e7

Observation 305af4a3-b7cc-457d-9b78-5f2855c60400 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.760408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.760408Z digest=sha256:ea291d0bd2550246c3709b7e6fb7910ba95f74c045a55779aa66b7c0383ba3c4

Observation 571ec81a-a1ef-4802-9c47-04070806ee80 · outbound

This paper cites Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Lift, splat, shoot: Encoding images from arbitrary camera rigs by implicitly unprojecting to 3d,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.764555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.764555Z digest=sha256:10c62f86140b29d718fb8e9820323fd5a15f6a208ff474ebf274e1dd996fde72

Observation 2a8dbdc7-b6c5-4b56-b2f6-4d3b8d6fb61c · outbound

This paper cites Bevdepth: Acquisition of reliable depth for multi-view 3d object detection,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Bevdepth: Acquisition of reliable depth for multi-view 3d object detection,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:02.935153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.768862Z digest=sha256:52d878610d380471aec6b50dc979bcc0a67b0c3ba327dfb5e8c32effbf7e40b8

Observation 792661d6-9ad0-432f-98d5-0b766da29444 · outbound

This paper cites Repair: Removing representation bias by dataset resampling,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Repair: Removing representation bias by dataset resampling,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:02.923041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.772881Z digest=sha256:893fbd2d13a70fc2309df7cbef2055e0c2fcc97e856c566cb093621df7f870f3

Observation 8b3f50c1-337b-492d-a565-01c569c3b9c1 · outbound

This paper cites Focal loss for dense object detection,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Focal loss for dense object detection,

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.777354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.777354Z digest=sha256:b1d1c5fa4e96728ad0ab6bff99ff0d6d4b6166e8cc3b18a487162a52fa307d1d

Observation c720f83e-76d0-4cfd-92a2-5d1b98ba3517 · outbound

This paper cites Second: Sparsely embedded convolutional detection,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Second: Sparsely embedded convolutional detection,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.781265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.781265Z digest=sha256:b0f377c91ad2cec5c38f589e8fb6967eb20b218a3918cecf0f31ca7b525cfb46

Observation 0d54995b-26a6-4bb2-9a42-9949e7673930 · outbound

This paper cites Deep high-resolution representation learning for visual recognition,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection Deep high-resolution representation learning for visual recognition,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:12:02.898412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-07T15:12:02.785742Z digest=sha256:6bc45f168f5f923e9907915d6ee8738e43e20de5953662e9538a9a796c2d7f1c

Observation 0ecbdfc1-0117-4bda-bf5d-119ff1beefa1 · outbound

This paper cites MOT16: A Benchmark for Multi-Object Tracking.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection MOT16: A Benchmark for Multi-Object Tracking

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.790168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.790168Z digest=sha256:16419e56dbfd8c0098f3ab3fa5a8477b3c4ddb8bf29411a96792b1f4870fd23d

Observation ab1dec03-2337-48f6-8b5c-d7679e89ca97 · outbound

This paper cites V oxelnext: Fully sparse voxelnet for 3d object detection and tracking,.

Learning better representations for crowded pedestrians in offboard LiDAR-camera 3D tracking-by-detection V oxelnext: Fully sparse voxelnet for 3d object detection and tracking,

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T15:12:02.794846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:12:02.794846Z digest=sha256:e46403e34f714fc6c610d11266ef6f8f717d66023a618d5f88091f44d5f5c137

Pith citing papers

No inbound Pith citation observations are available.