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Paper Citation Record · LEDGER

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions

As of 10 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2507.00648.

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

pith.paper-citation-record.v1
2507.00648 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:18:35.750104Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

55 of 55 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a1dc875b-8186-498c-824c-c663f21c1495 · outbound

This paper cites Ar- trackv2: Prompting autoregressive tracker where to look and how to describe.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Ar- trackv2: Prompting autoregressive tracker where to look and how to describe

Reference 1

Resolution
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Observation 9f70ccd9-49a9-4ca4-be4f-210335b202e6 · outbound

This paper cites Learning discriminative model prediction for track- ing.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Learning discriminative model prediction for track- ing

Reference 2

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Observation 8c52a87f-0655-4e70-85f0-6b02fb0f7230 · outbound

This paper cites Hiptrack: Vi- sual tracking with historical prompts.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Hiptrack: Vi- sual tracking with historical prompts

Reference 3

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Observation c02dbf67-9acd-4a32-a701-dcf88eaf8762 · outbound

This paper cites Robust object modeling for visual tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Robust object modeling for visual tracking

Reference 4

Resolution
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Source-reported events for the cited work

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Observation b7452db8-4296-4d91-b985-01de2bbe6e88 · outbound

This paper cites Seqtrack: Sequence to sequence learning for visual object tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Seqtrack: Sequence to sequence learning for visual object tracking

Reference 5

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Source-reported events for the cited work

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Observation 15b173e0-7f08-4a0e-bb81-43f577381f90 · outbound

This paper cites Siamese box adaptive network for visual tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Siamese box adaptive network for visual tracking

Reference 6

Resolution
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Source-reported events for the cited work

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Observation 97a7c70a-8cbf-4267-b39c-74397aa22f61 · outbound

This paper cites Optimal transport for domain adaptation.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Optimal transport for domain adaptation

Reference 7

Resolution
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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.

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Observation a540c1e8-d612-4819-837d-acf05bb59648 · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Sinkhorn distances: Lightspeed computation of optimal transport

Reference 8

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Source-reported events for the cited work

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Observation 15ace565-163a-4ed3-b4dc-02256c3a09bc · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions An image is worth 16x16 words: Transformers for image recognition at scale

Reference 9

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Source-reported events for the cited work

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Observation 36bbcc71-2e31-4e6a-b0b9-5b536823b118 · outbound

This paper cites Lasot: A high-quality benchmark for large-scale single object tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Lasot: A high-quality benchmark for large-scale single object tracking

Reference 10

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Source-reported events for the cited work

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Observation dbcf02bd-3685-4971-b545-35b6ce6abcc0 · outbound

This paper cites Highlightnet: Highlighting low-light potential features for real-time UA V tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Highlightnet: Highlighting low-light potential features for real-time UA V tracking

Reference 11

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Source-reported events for the cited work

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Observation b7d22c1f-c1cd-459d-bb18-c7da39ede3ec · outbound

This paper cites SAM-DA: UA V Tracks Anything at Night with SAM-Powered Domain Adaptation.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions SAM-DA: UA V Tracks Anything at Night with SAM-Powered Domain Adaptation

Reference 12

Resolution
verified fuzzy
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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.

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Observation a14631d6-3f7a-421b-a0c4-1d33047daff7 · outbound

This paper cites Expressive text-to-image generation with rich text.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Expressive text-to-image generation with rich text

Reference 13

Resolution
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Source-reported events for the cited work

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Observation 33623773-9dcd-4299-b731-26c008914538 · outbound

This paper cites Separable self and mixed attention transformers for efficient object tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Separable self and mixed attention transformers for efficient object tracking

Reference 14

Resolution
verified fuzzy
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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.

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Observation 1b312253-c7e6-4757-80b0-d17917c513e2 · outbound

This paper cites Visualizing data using t-sne journal of machine learning research.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Visualizing data using t-sne journal of machine learning research

Reference 15

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Source-reported events for the cited work

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Observation bd60b025-e771-4200-8ac4-acb95a5359ef · outbound

This paper cites SOOD: towards semi- supervised oriented object detection.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions SOOD: towards semi- supervised oriented object detection

Reference 16

Resolution
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Source-reported events for the cited work

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Observation ea2f0260-a73d-4b4e-b10a-0ebeed992040 · outbound

This paper cites Got-10k: A large high-diversity benchmark for generic object tracking in the wild.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Got-10k: A large high-diversity benchmark for generic object tracking in the wild

Reference 17

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Source-reported events for the cited work

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Observation e80d2524-822d-49e5-ab2e-14fa2c0dff6c · outbound

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UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Unresolved cited work

Reference 18

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Source-reported events for the cited work

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Observation aeee1519-6bc4-4c52-bc5f-46baacbdcbb7 · outbound

This paper cites Adtrack: Target-aware dual filter learning for real-time anti-dark UA V tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Adtrack: Target-aware dual filter learning for real-time anti-dark UA V tracking

Reference 19

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Source-reported events for the cited work

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Observation eab92a42-cf8f-470d-94ef-c31374cef24e · outbound

This paper cites Siamrpn++: Evolution of siamese visual tracking with very deep networks.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Siamrpn++: Evolution of siamese visual tracking with very deep networks

Reference 20

Resolution
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Source-reported events for the cited work

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Observation 03f27a9e-6e7a-47ed-806e-334ed9578856 · outbound

This paper cites High performance visual tracking with siamese region proposal network.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions High performance visual tracking with siamese region proposal network

Reference 21

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Source-reported events for the cited work

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Observation d37d1f90-6179-4840-a4e3-2d631be04678 · outbound

This paper cites Visual object tracking for un- manned aerial vehicles: A benchmark and new motion models.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Visual object tracking for un- manned aerial vehicles: A benchmark and new motion models

Reference 22

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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.

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Observation c50c65f7-05f3-4bc9-9aae-d70a0f0e5a05 · outbound

This paper cites Training-Free Model Merging for Multi-target Domain Adaptation.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Training-Free Model Merging for Multi-target Domain Adaptation

Reference 23

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Source-reported events for the cited work

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Observation 9cb90988-2679-4164-8f3a-a9e752aee3c3 · outbound

This paper cites Sigma: Semantic- complete graph matching for domain adaptive object detec- tion.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Sigma: Semantic- complete graph matching for domain adaptive object detec- tion

Reference 24

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Source-reported events for the cited work

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Observation c81498ac-f67f-49db-974f-27896400e0a8 · outbound

This paper cites Learning adaptive and view-invariant vision transformer for real-time uav tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Learning adaptive and view-invariant vision transformer for real-time uav tracking

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 49277b98-29ac-47de-b6fc-acbec48ae24b · outbound

This paper cites Microsoft coco: Common objects in context.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Microsoft coco: Common objects in context

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 738178a3-1397-4154-8885-e0bf1ea62e45 · outbound

This paper cites Breuel, and Jan Kautz.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Breuel, and Jan Kautz

Reference 27

Resolution
verified fuzzy
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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.

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Observation 3ca2c4fc-c3be-4aeb-8261-cfc2783855e2 · outbound

This paper cites Mutual-Learning Knowledge Distillation for Nighttime UAV Tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Mutual-Learning Knowledge Distillation for Nighttime UAV Tracking

Reference 28

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3ca8a324-9578-4f37-b0f2-f6df4d481995 · outbound

This paper cites Trackingnet: A large-scale dataset and benchmark for object tracking in the wild.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Trackingnet: A large-scale dataset and benchmark for object tracking in the wild

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:39.661713Z

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.

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Observation b5e3f2c7-e884-4418-b16a-d56d6df6d877 · outbound

This paper cites GLIDE: towards photorealistic image gen- eration and editing with text-guided diffusion models.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions GLIDE: towards photorealistic image gen- eration and editing with text-guided diffusion models

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:39.500287Z

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.

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Observation 3d174cec-3858-4abe-848c-bc31f4c868b6 · outbound

This paper cites Avist: A benchmark for visual object tracking in adverse visibility.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Avist: A benchmark for visual object tracking in adverse visibility

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:39.363526Z

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.

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Observation 4a6ac59d-5a32-4372-93eb-ced43d26f369 · outbound

This paper cites Zero-shot text-to-image generation.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Zero-shot text-to-image generation

Reference 32

Resolution
verified fuzzy
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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.

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Observation ffe1a454-6013-4668-9e13-33cd11ef8b03 · outbound

This paper cites Generalized in- tersection over union: A metric and a loss for bounding box regression.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Generalized in- tersection over union: A metric and a loss for bounding box regression

Reference 33

Resolution
verified fuzzy
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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.

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Observation f2e84d14-5415-45ae-9ec1-abd15520d19d · outbound

This paper cites Focal loss for dense ob- ject detection.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Focal loss for dense ob- ject detection

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:38.960009Z

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.

source=pdf_text observed=2026-08-06T21:18:34.149203Z digest=sha256:f4e3a5a55feed731d99c900555eeb2b3b4586a6685997e716e3b00b34ccdaa34

Observation ba862dd1-5cb9-434f-9bd3-5c39935e7f5e · outbound

This paper cites Curriculum graph co-teaching for multi- target domain adaptation.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Curriculum graph co-teaching for multi- target domain adaptation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:38.815562Z

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.

source=pdf_text observed=2026-08-06T21:18:34.222485Z digest=sha256:658a4a67fc5d40ee33a03936f2e78a1873fc8de779bc8c7065467474b2dca215

Observation 8298791c-b9bb-4e45-a65a-265753889cc3 · outbound

This paper cites Adversarial diffusion distillation.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Adversarial diffusion distillation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:38.657563Z

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.

source=pdf_text observed=2026-08-06T21:18:34.307274Z digest=sha256:44ae563cc6e704a4d6ff565fa9443f8fdcb38a39921f7aec9b69e7ebf08c4f4c

Observation b4680da1-dbce-4482-aca1-23a574687a66 · outbound

This paper cites Explicit visual prompts for visual object tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Explicit visual prompts for visual object tracking

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:38.491850Z

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.

source=pdf_text observed=2026-08-06T21:18:34.366340Z digest=sha256:b4ca322ce96ef5a3cea30c59604d62adf0c8acda8d0248542141549728f83852

Observation 3818e6f7-304b-4a22-a911-5fe955b73a75 · outbound

This paper cites Cross-modal pattern- propagation for RGB-T tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Cross-modal pattern- propagation for RGB-T tracking

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:38.363030Z

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.

source=pdf_text observed=2026-08-06T21:18:34.437708Z digest=sha256:926837e6b5e6d0c7703ab8404e1087d1309a80251830660f26329885c70e9ff3

Observation d3c68c48-62e7-4586-9f4e-8f8f7ccdaba5 · outbound

This paper cites Bovik, Hamid R.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Bovik, Hamid R

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:38.205659Z

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.

source=pdf_text observed=2026-08-06T21:18:34.544541Z digest=sha256:5d413cfcd830d2c52be1e72bab6a39ae9ddc1893a645bd6c75ee1cf9e638cf4d

Observation a825b701-71a3-4c90-b752-973cfa346667 · outbound

This paper cites Lvptrack: High per- formance domain adaptive UA V tracking with label aligned visual prompt tuning.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Lvptrack: High per- formance domain adaptive UA V tracking with label aligned visual prompt tuning

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:38.034747Z

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.

source=pdf_text observed=2026-08-06T21:18:34.598230Z digest=sha256:a1092218535ca761a24c04523b197ad0868b7fa7c131345ac7ee550724debf3e

Observation 7b597faf-8d04-45e1-9c83-3118bccee74f · outbound

This paper cites an unresolved cited work.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:18:37.869158Z

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.

source=pdf_text observed=2026-08-06T21:18:34.677584Z digest=sha256:3ac6e25723c5f00228ac4a509750db7c736693a05b14237af8c21ca19efd06a8

Observation 600b6f8c-1621-43ef-a2b8-47d48e6c77bb · outbound

This paper cites Autore- gressive queries for adaptive tracking with spatio-temporal transformers.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Autore- gressive queries for adaptive tracking with spatio-temporal transformers

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:37.701251Z

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.

source=pdf_text observed=2026-08-06T21:18:34.787351Z digest=sha256:e4f5502a72df63be9f38b85ab7fb72436ddf6d43397827264ee9f61030d004d9

Observation 61775eb0-1719-4e19-a3bf-098a67e848a2 · outbound

This paper cites Depthtrack: Un- veiling the power of RGBD tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Depthtrack: Un- veiling the power of RGBD tracking

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:37.566486Z

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.

source=pdf_text observed=2026-08-06T21:18:34.871154Z digest=sha256:6b55eb1165e69ad74af4f57aeb68c0ca337c02741c64d14debd2f78fd393a455

Observation 91cf556a-5034-4c3a-b25e-ed183300a370 · outbound

This paper cites Unctrack: Reliable visual object tracking with uncertainty-aware prototype memory network.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Unctrack: Reliable visual object tracking with uncertainty-aware prototype memory network

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:37.412798Z

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.

source=pdf_text observed=2026-08-06T21:18:34.979079Z digest=sha256:9eab7c28fb36afe9fae2cea117d468e3258b1abe93468675b5e8634ddde6d3ee

Observation 53bcb3e0-9a24-458a-81ec-91ed2b90e924 · outbound

This paper cites Learning deep lucas-kanade siamese network for visual tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Learning deep lucas-kanade siamese network for visual tracking

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:37.259200Z

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.

source=pdf_text observed=2026-08-06T21:18:35.062015Z digest=sha256:89b745f0469860ef7e54fcbfd568fda10d1feb3a957b7561459c5818c7a5e0ae

Observation c484a9ed-38d9-4b1b-a1da-d9ccb551b26f · outbound

This paper cites Robust online tracking via con- trastive spatio-temporal aware network.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Robust online tracking via con- trastive spatio-temporal aware network

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:37.132969Z

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.

source=pdf_text observed=2026-08-06T21:18:35.116375Z digest=sha256:d3bd34d1c70cd58b0e617da4cd907138c454c44cd7526d9b5e69229d4a4b3449

Observation f8e21fb7-b624-412a-9cd2-d638d49a6146 · outbound

This paper cites Joint feature learning and relation modeling for tracking: A one-stream framework.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Joint feature learning and relation modeling for tracking: A one-stream framework

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:36.986796Z

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.

source=pdf_text observed=2026-08-06T21:18:35.193630Z digest=sha256:37ecf7eba538d8604e4f4a1b4b8072997d9ab83c5e012746df9b2ac030eb6f40

Observation cf175a08-120e-4b1a-bb61-e0ab2af32283 · outbound

This paper cites Darklighter: Light up the darkness for UA V track- ing.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Darklighter: Light up the darkness for UA V track- ing

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:36.885876Z

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.

source=pdf_text observed=2026-08-06T21:18:35.288015Z digest=sha256:8233bb816f272328e4feec4f42be8d6e15d74582a7d1b8bfae301b1f58513bd5

Observation 16ecfd38-a849-4918-810e-db98dde67519 · outbound

This paper cites Unsupervised domain adaptation for nighttime aerial tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Unsupervised domain adaptation for nighttime aerial tracking

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:36.730293Z

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.

source=pdf_text observed=2026-08-06T21:18:35.342865Z digest=sha256:ee8644405fbf844328dca33783263bfbd246a1325b8963d09e9525344426266e

Observation 2e92f1f9-bf7f-4d1b-809f-842ada5eb197 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Adding conditional control to text-to-image diffusion models

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:36.566726Z

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.

source=pdf_text observed=2026-08-06T21:18:35.419809Z digest=sha256:dc30a5f2b3f2fa4996eb190f495cbb8714fe4caec4af398d0f098d6b64e12a0c

Observation eb8bdc73-71d7-4a6b-9b93-859b4bc8c9a0 · outbound

This paper cites Efros, Eli Shechtman, and Oliver Wang.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Efros, Eli Shechtman, and Oliver Wang

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:36.446348Z

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.

source=pdf_text observed=2026-08-06T21:18:35.494491Z digest=sha256:5eea3bf5be7fbf6f7755da56e8284463aa1e43a396158928897d0ab59b9b9144

Observation a2340b03-7a35-4a85-a71b-0f8ce5460e97 · outbound

This paper cites Domain Adaptive SiamRPN++ for Object Tracking in the Wild.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Domain Adaptive SiamRPN++ for Object Tracking in the Wild

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T21:18:35.548926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:18:35.548926Z digest=sha256:37c9c6e842138104819657414e047b40b8fc242cda815acacfa0443ec22f3371

Observation 79e9ea22-94d5-42c6-a05f-5bf317b0a01e · outbound

This paper cites Odtrack: Online dense temporal token learning for visual tracking.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Odtrack: Online dense temporal token learning for visual tracking

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:36.292083Z

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.

source=pdf_text observed=2026-08-06T21:18:35.621493Z digest=sha256:f8680493f43afba76df9285333d0cdb4a05f29927d876ad29501eb8ae2475f4a

Observation 3f6d04ef-9ac6-4b35-9f3b-c8408ff19a04 · outbound

This paper cites an unresolved cited work.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:18:36.128302Z

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.

source=pdf_text observed=2026-08-06T21:18:35.688186Z digest=sha256:76006e19f653e4e17e7e0c574e5d99d6be26ce38a35386b291c8b1f08aa8d159

Observation a254e0d0-7055-4644-b90f-3d137d02c982 · outbound

This paper cites DCPT: darkness clue-prompted tracking in nighttime uavs.

UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions DCPT: darkness clue-prompted tracking in nighttime uavs

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:18:35.960280Z

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.

source=pdf_text observed=2026-08-06T21:18:35.750104Z digest=sha256:0a03271cc4ff1112aa4cb5cf559e6eef4371b16ab3489998e65cad2a38abfb96

Pith citing papers

No inbound Pith citation observations are available.