MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning | Paper Citation Record

Observation 685cad98-0207-4e46-aa81-cc25cff215a8 · outbound

This paper cites Uav assisted usv visual navigation for marine mass casualty incident response,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Uav assisted usv visual navigation for marine mass casualty incident response,

Reference 1

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Observation 14fb33d1-f8e3-444d-a55a-3c44c774d79c · outbound

This paper cites Video processing techniques for traffic flow monitoring: A survey,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Video processing techniques for traffic flow monitoring: A survey,

Reference 2

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Observation 0ac34fb3-8de9-41b8-ad99-110e9ef0f340 · outbound

This paper cites On the visual-based safe landing of uavs in populated areas: a crucial aspect for urban deployment,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning On the visual-based safe landing of uavs in populated areas: a crucial aspect for urban deployment,

Reference 3

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Observation 5233223f-0108-401a-b99e-d4fa0a72169b · outbound

This paper cites Imagenet classifica- tion with deep convolutional neural networks,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Imagenet classifica- tion with deep convolutional neural networks,

Reference 4

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Observation 94dc1c17-7962-4115-b515-ce60ebd272ae · outbound

This paper cites Deep residual learning for image recognition,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Deep residual learning for image recognition,

Reference 5

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Observation f5f5bfbc-bd93-40e3-8d93-eed332ee40d5 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 6

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Observation 7e987f29-7346-427b-9ab6-ba070d08b430 · outbound

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

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Lasot: A high-quality benchmark for large- scale single object tracking,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.198732Z

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Observation ed061b60-206e-4a92-a315-d1ef7915cd59 · outbound

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

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Got-10k: A large high-diversity benchmark for generic object tracking in the wild,

Reference 8

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Observation 3850de15-510d-41e3-a893-7a9de4e656f6 · outbound

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

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Trackingnet: A large-scale dataset and benchmark for object tracking in the wild,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.180220Z

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Observation deb0eb1a-0543-4cb1-9661-e81cbb0ce32d · outbound

This paper cites Tctrack: Temporal contexts for aerial tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Tctrack: Temporal contexts for aerial tracking,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.170699Z

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Observation 02c818ab-d7cc-4ff0-b7eb-d6cbeb1e7f2e · outbound

This paper cites Adaptive and background-aware vision transformer for real-time uav tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Adaptive and background-aware vision transformer for real-time uav tracking,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.160574Z

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Observation 91a52c57-2ebb-4fad-8dd2-173f95490380 · outbound

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

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Learning adaptive and view-invariant vision transformer for real-time uav tracking,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.151189Z

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Observation 93cd7c96-83e1-4a02-a5f3-af4e93a768e4 · outbound

This paper cites Unsupervised domain adaptation for nighttime aerial tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Unsupervised domain adaptation for nighttime aerial tracking,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.142302Z

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Observation 3639dad6-7819-4f7a-9704-889126b45367 · outbound

This paper cites Prompt-Driven Temporal Domain Adaptation for Nighttime UAV Tracking.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Prompt-Driven Temporal Domain Adaptation for Nighttime UAV Tracking

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:14:58.822569Z

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Observation e0f2781d-157b-441d-aa5a-c2d78708d09f · outbound

This paper cites Darklighter: Light up the darkness for uav tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Darklighter: Light up the darkness for uav tracking,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.133115Z

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Observation 7362f347-2b14-4936-8898-07346a070fee · outbound

This paper cites Tracker meets night: A transformer enhancer for uav tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Tracker meets night: A transformer enhancer for uav tracking,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.122648Z

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Observation 1fcefd19-5ca4-4ffb-8a24-bc1c84f2f8d5 · outbound

This paper cites Enhancing Nighttime UAV Tracking with Light Distribution Suppression.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Enhancing Nighttime UAV Tracking with Light Distribution Suppression

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:14:58.810248Z

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Observation a3f5518a-9f05-426e-a83f-bb3b9f22239c · outbound

This paper cites Sam-da: Uav tracks anything at night with sam-powered domain adaptation,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Sam-da: Uav tracks anything at night with sam-powered domain adaptation,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.112315Z

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Observation bcf464ae-03a3-4000-a182-0cd46b4ae4b4 · outbound

This paper cites Dcpt: Darkness clue-prompted tracking in nighttime uavs,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Dcpt: Darkness clue-prompted tracking in nighttime uavs,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.102534Z

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Observation 1c1e6c4b-7ac4-4e95-9a33-c64d2cee1abf · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 20

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Observation ee44ba62-509e-41d2-b805-86f5ea6d8118 · outbound

This paper cites VideoMamba: State Space Model for Efficient Video Understanding.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning VideoMamba: State Space Model for Efficient Video Understanding

Reference 21

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Observation 0d882893-fce8-4449-a1d9-3ea55843e45e · outbound

This paper cites VM-UNet: Vision Mamba UNet for Medical Image Segmentation.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning VM-UNet: Vision Mamba UNet for Medical Image Segmentation

Reference 22

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Observation c91e8f68-c1b5-4453-9371-075b99ff8df2 · outbound

This paper cites Cost-sensitive learning of deep feature representations from imbal- anced data,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Cost-sensitive learning of deep feature representations from imbal- anced data,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.093444Z

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Observation f5a18c85-8c51-4c24-9d6c-4f09d2c651a6 · outbound

This paper cites Shift: a synthetic driving dataset for continuous multi-task domain adaptation,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Shift: a synthetic driving dataset for continuous multi-task domain adaptation,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.083542Z

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Observation 8103ddc7-6be6-4378-9867-03e6af7c69a3 · outbound

This paper cites Getting to know low-light images with the exclusively dark dataset,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Getting to know low-light images with the exclusively dark dataset,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.074115Z

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Observation db11245b-fbe5-4237-a264-26f8658e80b7 · outbound

This paper cites Bdd100k: A diverse driving dataset for heterogeneous multitask learning,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Bdd100k: A diverse driving dataset for heterogeneous multitask learning,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.065149Z

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Observation 38290e26-9098-44e8-b8cf-d0d19cf88ab6 · outbound

This paper cites Learning from imbalanced data,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Learning from imbalanced data,

Reference 27

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Observation 8e3ab7f5-6b65-46c1-a8cc-f2600ac8a143 · outbound

This paper cites Classification with rejection based on cost-sensitive classification,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Classification with rejection based on cost-sensitive classification,

Reference 28

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Observation ab5fc48b-496b-4229-98d8-65314ba4a5a9 · outbound

This paper cites Curriculum learning,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Curriculum learning,

Reference 29

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Observation 37cf9720-90cd-45f3-b25f-0a3cd9e3f42b · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Efficiently Modeling Long Sequences with Structured State Spaces

Reference 30

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Observation eb1a1f18-45e6-4d6d-a834-a9d8a6be9d91 · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 31

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Observation 016c7cb2-9f5d-4be4-a83e-ee7643c0d443 · outbound

This paper cites VMamba: Visual State Space Model.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning VMamba: Visual State Space Model

Reference 32

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Observation 9ae2b0be-b6d0-47bb-8ea0-4a216f6ec729 · outbound

This paper cites Swin-umamba: Mamba-based unet with imagenet-based pretraining,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Swin-umamba: Mamba-based unet with imagenet-based pretraining,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.031668Z

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Observation e3f48cd6-3917-49dc-b8c6-548c77116274 · outbound

This paper cites MambaTrack: A Simple Baseline for Multiple Object Tracking with State Space Model.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning MambaTrack: A Simple Baseline for Multiple Object Tracking with State Space Model

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:14:58.751510Z

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Observation f67f7980-21f4-48b2-8e05-1b2e6a43b5a9 · outbound

This paper cites Teaching classification boundaries to humans,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Teaching classification boundaries to humans,

Reference 35

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Observation 5d18a56f-6efd-449c-b0c6-3c2b7d272088 · outbound

This paper cites On the power of curriculum learning in training deep networks,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning On the power of curriculum learning in training deep networks,

Reference 36

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Observation 1349bd88-8ea1-4470-8a90-a3762b71b862 · outbound

This paper cites How do humans teach: On curriculum learning and teaching dimension,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning How do humans teach: On curriculum learning and teaching dimension,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:59.006899Z

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Observation f6a863d2-03ce-4bdc-9b38-a1e2a5903224 · outbound

This paper cites Self-paced learning for latent variable models,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Self-paced learning for latent variable models,

Reference 38

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Observation 09123cf3-c0c7-41cd-a849-b9b5b017ff30 · outbound

This paper cites Dynamic curriculum learning for imbalanced data classification,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Dynamic curriculum learning for imbalanced data classification,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.987606Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b15fef82-1803-4c80-970a-c62051f4bcc9 · outbound

This paper cites Semi-supervised action recognition from temporal augmentation using curriculum learning,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Semi-supervised action recognition from temporal augmentation using curriculum learning,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.977168Z

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Observation af58785a-bca3-4bbc-b021-c08fc3b76bc9 · outbound

This paper cites Bridging Saliency Detection to Weakly Supervised Object Detection Based on Self-paced Curriculum Learning.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Bridging Saliency Detection to Weakly Supervised Object Detection Based on Self-paced Curriculum Learning

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:14:58.738764Z

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Observation 1e92ea9c-7674-4926-9286-aca252c11d5e · outbound

This paper cites Curriculum self- paced learning for cross-domain object detection,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Curriculum self- paced learning for cross-domain object detection,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.968011Z

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Observation dabd3241-3d3f-4cd0-9eda-e59216f9b07f · outbound

This paper cites A new approach to linear filtering and prediction problems,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning A new approach to linear filtering and prediction problems,

Reference 43

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Observation 1a2679a4-6cb1-40fd-81dc-e96a83e63b7b · outbound

This paper cites Dynamically weighted bal- anced loss: class imbalanced learning and confidence calibration of deep neural networks,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Dynamically weighted bal- anced loss: class imbalanced learning and confidence calibration of deep neural networks,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.952675Z

Source-reported events for the cited work

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Observation 0d37cd1b-ba15-4c90-a79f-07472a93af98 · outbound

This paper cites All-day object tracking for unmanned aerial vehicle,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning All-day object tracking for unmanned aerial vehicle,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.943366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d0e4362e-559a-48c9-b158-46c4f08fb45c · outbound

This paper cites SGDViT: Saliency-Guided Dynamic Vision Transformer for UAV Tracking.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning SGDViT: Saliency-Guided Dynamic Vision Transformer for UAV Tracking

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T05:14:58.641521Z

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Observation 2720f0d0-a170-4738-bdbe-31930c39ead0 · outbound

This paper cites Exploring lightweight hierarchical vision transformers for efficient visual tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Exploring lightweight hierarchical vision transformers for efficient visual tracking,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.934483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ae1d0457-40c3-4f6a-b375-b3694d1cb9d2 · outbound

This paper cites Representation learning for visual object tracking by masked appearance transfer,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Representation learning for visual object tracking by masked appearance transfer,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.925476Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 52481405-e87c-40b7-b732-29b21109f066 · outbound

This paper cites Towards real- world visual tracking with temporal contexts,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Towards real- world visual tracking with temporal contexts,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.916273Z

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Observation 4835d3cf-0345-4091-bf82-7d31133e7500 · outbound

This paper cites Hift: Hierarchical feature transformer for aerial tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Hift: Hierarchical feature transformer for aerial tracking,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.906586Z

Source-reported events for the cited work

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Observation af6b2521-6343-4014-8c10-ffa336590278 · outbound

This paper cites Siamapn++: Siamese attentional aggregation network for real-time uav tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Siamapn++: Siamese attentional aggregation network for real-time uav tracking,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.898074Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 24d9ce03-f6cb-4f59-82aa-28c24820aa94 · outbound

This paper cites Siamcar: Siamese fully convolutional classification and regression for visual tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Siamcar: Siamese fully convolutional classification and regression for visual tracking,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.888579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b9aa33d5-d5c0-4ead-9010-b63de7478105 · outbound

This paper cites Ocean: Object-aware anchor-free tracking,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Ocean: Object-aware anchor-free tracking,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.879476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 280f1094-8053-4d3d-bfeb-9f6c7eabd506 · outbound

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

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Joint feature learning and relation modeling for tracking: A one-stream framework,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.870803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 74a3be9a-5171-4576-8a76-0c86e168073e · outbound

This paper cites Cornernet: Detecting objects as paired key- points,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Cornernet: Detecting objects as paired key- points,

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T05:14:58.669922Z

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Unavailable: canonical work link unavailable.

Observation 444125c1-b7ef-48a1-bed0-c1f13786c07b · outbound

This paper cites Generalized intersection over union: A metric and a loss for bounding box regression,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Generalized intersection over union: A metric and a loss for bounding box regression,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.857161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cce452d7-004e-4dfa-8f95-c95060327aba · outbound

This paper cites Mamba-R: Vision Mamba ALSO Needs Registers.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Mamba-R: Vision Mamba ALSO Needs Registers

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-12T05:14:58.675914Z

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Unavailable: canonical work link unavailable.

Observation 39b1fb1e-70b2-4ce4-a36b-b7c6a8920830 · outbound

This paper cites Microsoft coco: Common objects in context,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Microsoft coco: Common objects in context,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.847957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9a3dbf14-deaf-4b5b-847c-5894c1286894 · outbound

This paper cites Focal Loss for Dense Object Detection.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Focal Loss for Dense Object Detection

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T05:14:58.681912Z

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Unavailable: canonical work link unavailable.

Observation 8db2d7bb-884e-405c-8a44-e3b2de2b9efa · outbound

This paper cites Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations,.

MambaNUT: Nighttime UAV Tracking via Mamba-based Adaptive Curriculum Learning Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:14:58.838999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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