A Simple Detector with Frame Dynamics is a Strong Tracker | Paper Citation Record

Observation 0fa1ac7f-36f3-44c3-a2a5-9f3eaacbc20f · outbound

This paper cites YOLOv11 for Vehicle Detection: Advancements, Performance, and Applications in Intelligent Transportation Systems.

A Simple Detector with Frame Dynamics is a Strong Tracker YOLOv11 for Vehicle Detection: Advancements, Performance, and Applications in Intelligent Transportation Systems

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.186774Z

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Observation 8a367a5b-8f3c-4c42-af0b-1f2c1605a2c2 · outbound

This paper cites Cascade r-cnn: Delv- ing into high quality object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Cascade r-cnn: Delv- ing into high quality object detection

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.325044Z

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Observation 9fe059fc-3c52-47fa-a72a-66cd49130af6 · outbound

This paper cites Backbone is all your need: A simplified architecture for visual object tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Backbone is all your need: A simplified architecture for visual object tracking

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.307571Z

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Observation 94141a07-c0bd-4310-b9ed-fa55bc6631f5 · outbound

This paper cites Seqtrack: Sequence to sequence learning for visual ob- ject tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Seqtrack: Sequence to sequence learning for visual ob- ject tracking

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.292729Z

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Observation 8b823eba-0b3d-49c8-b6e6-26b42dd2aff6 · outbound

This paper cites Transformer tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Transformer tracking

Reference 5

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Observation e0b6775e-776c-4314-834c-81c367ba1cbc · outbound

This paper cites Mixformer: End-to-end tracking with iterative mixed atten- tion.

A Simple Detector with Frame Dynamics is a Strong Tracker Mixformer: End-to-end tracking with iterative mixed atten- tion

Reference 6

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Observation c5aea8c2-28fb-4db8-b825-de36519640b6 · outbound

This paper cites One-stage cascade refinement networks for infrared small target detection.

A Simple Detector with Frame Dynamics is a Strong Tracker One-stage cascade refinement networks for infrared small target detection

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.252581Z

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Observation 0e772e56-bdf6-4dc4-8f91-291087888bb7 · outbound

This paper cites Pick of the bunch: Detecting infrared small targets beyond hit-miss trade-offs via selective rank-aware attention.

A Simple Detector with Frame Dynamics is a Strong Tracker Pick of the bunch: Detecting infrared small targets beyond hit-miss trade-offs via selective rank-aware attention

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.237538Z

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Observation 923c72cb-f8da-40ea-a9c3-5a9b9b6f04d7 · outbound

This paper cites Superpoint: Self-supervised interest point detection and description.

A Simple Detector with Frame Dynamics is a Strong Tracker Superpoint: Self-supervised interest point detection and description

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.221591Z

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Observation 5c1cd01c-f110-44f9-994f-3dadc7fcb2ee · outbound

This paper cites Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks.

A Simple Detector with Frame Dynamics is a Strong Tracker Use HiResCAM instead of Grad-CAM for faithful explanations of convolutional neural networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.225508Z

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Observation 6f0ae533-c3ef-4c43-a62e-4ab41fe49d09 · outbound

This paper cites Centernet: Keypoint triplets for object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Centernet: Keypoint triplets for object detection

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.229764Z

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Observation a76d356b-d958-4677-87b2-463d6deb5c65 · outbound

This paper cites Querytrack: joint-modality query fusion net- work for rgbt tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Querytrack: joint-modality query fusion net- work for rgbt tracking

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.203481Z

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Observation f11e334a-e999-4aed-b3fc-0eb0591f80ae · outbound

This paper cites Tood: Task-aligned one-stage object detec- tion.

A Simple Detector with Frame Dynamics is a Strong Tracker Tood: Task-aligned one-stage object detec- tion

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.188778Z

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Observation 48f4f1ba-0752-427d-8d4f-c1ff9f356380 · outbound

This paper cites Generalized relation modeling for transformer tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Generalized relation modeling for transformer tracking

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.174031Z

Source-reported events for the cited work

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Observation 59b9c26a-dfd8-4f7d-a961-97290eb28c6a · outbound

This paper cites Fast r-cnn.

A Simple Detector with Frame Dynamics is a Strong Tracker Fast r-cnn

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.245643Z

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Observation 545ebaca-7112-427d-b0bd-1e908cbbcd46 · outbound

This paper cites A twofold siamese network for real-time object tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker A twofold siamese network for real-time object tracking

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.149661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1828bfd0-a860-43b0-8a9d-0cb32370ee67 · outbound

This paper cites Motion matters: Difference-based multi- scale learning for infrared uav detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Motion matters: Difference-based multi- scale learning for infrared uav detection

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.134913Z

Source-reported events for the cited work

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Observation ff5b417d-2fcb-4277-a346-60a9663267a7 · outbound

This paper cites Determining opti- cal flow.

A Simple Detector with Frame Dynamics is a Strong Tracker Determining opti- cal flow

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.119602Z

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Observation 61012649-8ad7-4033-97fc-5043320917ad · outbound

This paper cites an unresolved cited work.

A Simple Detector with Frame Dynamics is a Strong Tracker Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-15T23:22:08.105590Z

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Observation 90c2ecd5-d5d0-48e1-aea1-fc24ef36991a · outbound

This paper cites Globaltrack: A simple and strong baseline for long-term tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Globaltrack: A simple and strong baseline for long-term tracking

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.089394Z

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Observation 9de76b73-a613-4e44-92cd-4812e2103771 · outbound

This paper cites Anti-UAV: A Large Multi-Modal Benchmark for UAV Tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Anti-UAV: A Large Multi-Modal Benchmark for UAV Tracking

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.269348Z

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Observation df6c2a1b-c7c0-4fa9-ac4b-52d8d25492b4 · outbound

This paper cites Asf-yolo: A novel yolo model with attentional scale sequence fusion for cell instance segmentation.

A Simple Detector with Frame Dynamics is a Strong Tracker Asf-yolo: A novel yolo model with attentional scale sequence fusion for cell instance segmentation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.076073Z

Source-reported events for the cited work

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Observation 527d1d01-5530-46a6-a2b9-4ca1506d2b4b · outbound

This paper cites YOLOv11: An Overview of the Key Architectural Enhancements.

A Simple Detector with Frame Dynamics is a Strong Tracker YOLOv11: An Overview of the Key Architectural Enhancements

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.277523Z

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Observation 84f3cfa7-17e0-4733-bcc7-cd1aa6076247 · outbound

This paper cites Probabilistic anchor assign- ment with iou prediction for object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Probabilistic anchor assign- ment with iou prediction for object detection

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.061904Z

Source-reported events for the cited work

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Observation 7f9f96b7-1547-4efe-8716-605a6e6b5d53 · outbound

This paper cites Slim-neck by GSConv: A lightweight-design for real-time detector architectures.

A Simple Detector with Frame Dynamics is a Strong Tracker Slim-neck by GSConv: A lightweight-design for real-time detector architectures

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-15T23:22:07.627120Z

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Observation fba20241-c997-47c9-9cf5-584dc665945b · outbound

This paper cites Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Generalized focal loss: Learning qualified and distributed bounding boxes for dense object detection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.047536Z

Source-reported events for the cited work

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Observation ebb206f4-04c6-4fef-af1d-e9a1f28030ed · outbound

This paper cites Lsknet: A foundation lightweight backbone for remote sensing.

A Simple Detector with Frame Dynamics is a Strong Tracker Lsknet: A foundation lightweight backbone for remote sensing

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.033029Z

Source-reported events for the cited work

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Observation 89393c4a-7a3c-4825-be6c-6d2fa57b267c · outbound

This paper cites Tracking meets lora: Faster training, larger model, stronger performance.

A Simple Detector with Frame Dynamics is a Strong Tracker Tracking meets lora: Faster training, larger model, stronger performance

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.301925Z

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Unavailable: canonical work link unavailable.

Observation 65724584-3692-4b5f-83a5-d1598b7b2ee4 · outbound

This paper cites Swintrack: A simple and strong baseline for trans- former tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Swintrack: A simple and strong baseline for trans- former tracking

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:08.008354Z

Source-reported events for the cited work

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Observation c43b9ab6-eddc-41d0-b572-f8052709acbd · outbound

This paper cites Focal loss for dense object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Focal loss for dense object detection

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.993383Z

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Observation ce321d9d-06d8-4eda-bf6f-6e132d093613 · outbound

This paper cites Lightglue: Local feature matching at light speed.

A Simple Detector with Frame Dynamics is a Strong Tracker Lightglue: Local feature matching at light speed

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.977604Z

Source-reported events for the cited work

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Observation b9a78546-59a6-4a46-af93-df7120be9095 · outbound

This paper cites Path aggregation network for instance segmentation.

A Simple Detector with Frame Dynamics is a Strong Tracker Path aggregation network for instance segmentation

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.962111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 73934611-f0f2-4afa-b19b-d6250937b3d1 · outbound

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

A Simple Detector with Frame Dynamics is a Strong Tracker Swin transformer: Hierarchical vision transformer using shifted windows

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.325134Z

Source-reported events for the cited work

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Observation 77ff6fb5-9388-44a1-9544-a7ce0c608286 · outbound

This paper cites Libra r-cnn: Towards balanced learning for object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Libra r-cnn: Towards balanced learning for object detection

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.329502Z

Source-reported events for the cited work

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Observation 72bf326e-0117-486c-9a40-616cc91fb1c5 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

A Simple Detector with Frame Dynamics is a Strong Tracker Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.333490Z

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Observation 163d5c13-15ab-467c-be15-9ddeec7e324d · outbound

This paper cites No more strided convolutions or pooling: A new CNN building block for low-resolution im- ages and small objects.

A Simple Detector with Frame Dynamics is a Strong Tracker No more strided convolutions or pooling: A new CNN building block for low-resolution im- ages and small objects

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.919421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8663102f-6e25-4773-82f2-3fdccd82c984 · outbound

This paper cites Fcos: Fully convolutional one-stage object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Fcos: Fully convolutional one-stage object detection

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.904624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 70732600-cbbc-43bc-98df-af9051017a48 · outbound

This paper cites Attention is all you need.

A Simple Detector with Frame Dynamics is a Strong Tracker Attention is all you need

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.345797Z

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Observation 91840409-a5a1-45c1-961d-6093072bdc94 · outbound

This paper cites Optical flow in deep visual tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Optical flow in deep visual tracking

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.881056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 058ca9ed-1c73-4b9f-8483-f05b35101418 · outbound

This paper cites Siam r-cnn: Visual tracking by re-detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Siam r-cnn: Visual tracking by re-detection

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.867625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 575eae69-45ef-4b32-bcf8-9d652473aa47 · outbound

This paper cites Pvt v2: Improved baselines with pyramid vision transformer.

A Simple Detector with Frame Dynamics is a Strong Tracker Pvt v2: Improved baselines with pyramid vision transformer

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.854055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 75d696c4-6159-45f0-97c8-18841b86d414 · outbound

This paper cites Con- vnext v2: Co-designing and scaling convnets with masked autoencoders.

A Simple Detector with Frame Dynamics is a Strong Tracker Con- vnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.839967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0f64e088-0932-47e9-b38c-18045ef444ed · outbound

This paper cites Pfinder: Real-time tracking of the human body.

A Simple Detector with Frame Dynamics is a Strong Tracker Pfinder: Real-time tracking of the human body

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.826268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f5fc822b-c631-4e7b-87f7-bfb27125b2d8 · outbound

This paper cites Dropmae: Masked autoen- coders with spatial-attention dropout for tracking tasks.

A Simple Detector with Frame Dynamics is a Strong Tracker Dropmae: Masked autoen- coders with spatial-attention dropout for tracking tasks

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.812023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation edbc11b5-f54e-4a44-94a0-26c830cefbe3 · outbound

This paper cites Back- ground semantics matter: Cross-task feature exchange net- work for clustered infrared small target detection with sky- annotated dataset.

A Simple Detector with Frame Dynamics is a Strong Tracker Back- ground semantics matter: Cross-task feature exchange net- work for clustered infrared small target detection with sky- annotated dataset

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.374187Z

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Observation a85f9608-decd-40b8-a53a-a37a4b61d4eb · outbound

This paper cites Learning spatio-temporal transformer for vi- sual tracking.

A Simple Detector with Frame Dynamics is a Strong Tracker Learning spatio-temporal transformer for vi- sual tracking

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.796567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 02ca7ec0-736c-4ecc-87b3-fce5c2645c85 · outbound

This paper cites Afpn: Asymptotic feature pyra- mid network for object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Afpn: Asymptotic feature pyra- mid network for object detection

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.782082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c8f8ffbf-67ce-4f0f-9be5-94589243c13a · outbound

This paper cites MHAF-YOLO: Multi-Branch Heterogeneous Auxiliary Fusion YOLO for accurate object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker MHAF-YOLO: Multi-Branch Heterogeneous Auxiliary Fusion YOLO for accurate object detection

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.385388Z

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Unavailable: canonical work link unavailable.

Observation d5a3e4f2-a23c-42ed-921c-3c06f4592523 · outbound

This paper cites Reppoints: Point set representation for object detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Reppoints: Point set representation for object detection

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.767275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 322e9b4e-6000-4d91-8320-3ac357d3b708 · outbound

This paper cites Joint feature learning and relation modeling for 10 tracking: A one-stream framework.

A Simple Detector with Frame Dynamics is a Strong Tracker Joint feature learning and relation modeling for 10 tracking: A one-stream framework

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.751681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6135c236-30f1-4a10-9963-a4e38e6bdfda · outbound

This paper cites Sctransnet: Spatial-channel cross transformer net- work for infrared small target detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Sctransnet: Spatial-channel cross transformer net- work for infrared small target detection

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.737180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 49acff50-0467-4f3d-bf8b-ff4fb758b3a5 · outbound

This paper cites Dynamic r-cnn: Towards high quality object detection via dynamic training.

A Simple Detector with Frame Dynamics is a Strong Tracker Dynamic r-cnn: Towards high quality object detection via dynamic training

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.401641Z

Source-reported events for the cited work

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Observation b6df296b-e3d4-44f6-8440-5ad1e66b51cf · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

A Simple Detector with Frame Dynamics is a Strong Tracker DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.405168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea91c7e7-e18d-4872-9b04-4e3866495d84 · outbound

This paper cites Varifocalnet: An iou-aware dense object detector.

A Simple Detector with Frame Dynamics is a Strong Tracker Varifocalnet: An iou-aware dense object detector

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T23:22:07.712110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3495a55a-7038-4b2b-addd-bee498c1567f · outbound

This paper cites Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection.

A Simple Detector with Frame Dynamics is a Strong Tracker Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.412666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3448638d-9497-40b8-970b-baf53f8de1e6 · outbound

This paper cites The 3rd Anti-UAV Workshop & Challenge: Methods and Results.

A Simple Detector with Frame Dynamics is a Strong Tracker The 3rd Anti-UAV Workshop & Challenge: Methods and Results

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.416424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c3ffd54-f52a-49a0-b93d-823d45f32639 · outbound

This paper cites AutoAssign: Differentiable Label Assignment for Dense Object Detection.

A Simple Detector with Frame Dynamics is a Strong Tracker AutoAssign: Differentiable Label Assignment for Dense Object Detection

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.420532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be4cdeb6-d490-48d2-8cac-d1321c90df14 · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

A Simple Detector with Frame Dynamics is a Strong Tracker Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T23:22:07.424466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers