CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking | Paper Citation Record

Observation 7f2b152a-224b-468d-a290-447daca15b2d · outbound

This paper cites Bootstrapping referring multi-object tracking.arXiv preprint arXiv:2406.05039, 2024.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Bootstrapping referring multi-object tracking.arXiv preprint arXiv:2406.05039, 2024

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.443509Z

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Observation e163dff7-f640-4853-b989-f66b98dc798d · outbound

This paper cites Simple online and realtime tracking.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Simple online and realtime tracking

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.448177Z

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Observation cc7f5520-67f9-4f9b-82e2-834b92c73f6d · outbound

This paper cites Simple online and realtime tracking with a deep association metric.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Simple online and realtime tracking with a deep association metric

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.452070Z

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Observation 2ccf04c7-0d6d-4181-bda0-5265fa3f91ed · outbound

This paper cites Tracking without bells and whistles.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Tracking without bells and whistles

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.456278Z

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Observation 36002f61-60ac-4a6f-af6a-a285911ae31c · outbound

This paper cites Tracking objects as points.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Tracking objects as points

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.460407Z

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Observation c23b4661-7281-460a-a16c-04e045d3a6c4 · outbound

This paper cites FairMOT: On the fairness of detection and re-identification in multiple object tracking.International Journal of Computer Vision, 129:3069–3087, 2021.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking FairMOT: On the fairness of detection and re-identification in multiple object tracking.International Journal of Computer Vision, 129:3069–3087, 2021

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.464743Z

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Observation 076c04f8-d424-46fd-9942-e687a9b7a05b · outbound

This paper cites ByteTrack: Multi-object tracking by associating every detection box.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking ByteTrack: Multi-object tracking by associating every detection box

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.469151Z

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Observation 4f82ac7f-123d-4827-bd54-919be6ba36ff · outbound

This paper cites Observation- centric SORT: Rethinking SORT for robust multi-object tracking.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Observation- centric SORT: Rethinking SORT for robust multi-object tracking

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.473273Z

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Observation 19ab0299-9d21-4548-8453-119380b58125 · outbound

This paper cites TransTrack: Multiple Object Tracking with Transformer.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking TransTrack: Multiple Object Tracking with Transformer

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.476807Z

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Observation 7dc91ea8-5153-4a83-b5c6-e3d2f93bc869 · outbound

This paper cites Track- Former: Multi-object tracking with transformers.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Track- Former: Multi-object tracking with transformers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.480893Z

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Observation f4173593-8ee7-471a-88c3-504a65c9dcff · outbound

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

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking MOTR: End-to-end multiple-object tracking with transformer

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.484901Z

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Observation 1d84f841-943c-45be-b8e5-92023ee14dd9 · outbound

This paper cites MOTRv2: Bootstrapping end-to-end multi- object tracking by pretrained object detectors.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking MOTRv2: Bootstrapping end-to-end multi- object tracking by pretrained object detectors

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.488670Z

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Observation b0c8d38e-6d70-4eec-a818-d82e5e35a308 · outbound

This paper cites Towards grand unification of object tracking.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Towards grand unification of object tracking

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.492354Z

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Observation 9bd7ce12-7001-4b3d-b835-f8feb83f3cf8 · outbound

This paper cites Referring multi-object tracking.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Referring multi-object tracking

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.495878Z

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Observation 8cc53bf5-0f3c-4c1a-a9e2-c1abe499f48e · outbound

This paper cites iKUN: Speak to trackers without retraining.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking iKUN: Speak to trackers without retraining

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.499321Z

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Observation 2dfd4995-7336-4100-8a0d-75f003c4db80 · outbound

This paper cites EchoTrack: Auditory referring multi-object tracking for autonomous driving.IEEE Transactions on Intelligent Transportation Systems, 25(11):18964–18977, 2024.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking EchoTrack: Auditory referring multi-object tracking for autonomous driving.IEEE Transactions on Intelligent Transportation Systems, 25(11):18964–18977, 2024

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.503168Z

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Observation a1e1f980-26a7-4321-b41b-d49dc6d701c1 · outbound

This paper cites Visual-linguistic representation learning with deep cross-modality fusion for referring multi-object tracking.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Visual-linguistic representation learning with deep cross-modality fusion for referring multi-object tracking

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.506806Z

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Observation 2f7a4dd2-d47c-45a9-8a35-ffb9e0fad126 · outbound

This paper cites Multigranularity local- ization transformer with collaborative understanding for referring multiobject tracking.IEEE Transactions on Instrumentation and Measurement, 74:1–13, 2025.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Multigranularity local- ization transformer with collaborative understanding for referring multiobject tracking.IEEE Transactions on Instrumentation and Measurement, 74:1–13, 2025

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.510400Z

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Observation a8cc7106-f812-4cda-bab3-5affa6a26b68 · outbound

This paper cites Language decoupling with fine-grained knowledge guidance for referring multi-object tracking.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Language decoupling with fine-grained knowledge guidance for referring multi-object tracking

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.513948Z

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Observation 4d8e125d-2c70-497b-a7d2-3c3f371f6543 · outbound

This paper cites ReaMOT: A Benchmark and Framework for Reasoning-based Multi-Object Tracking.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking ReaMOT: A Benchmark and Framework for Reasoning-based Multi-Object Tracking

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.517786Z

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Observation 17cb7be0-42c5-4d76-a21a-99ab6da3a235 · outbound

This paper cites ReferGPT: Towards zero-shot referring multi-object tracking.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking ReferGPT: Towards zero-shot referring multi-object tracking

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.521901Z

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Observation 137ee511-da8f-4334-919c-e7f2b2ac6517 · outbound

This paper cites End-to-end referring video object segmentation with multimodal transformers.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking End-to-end referring video object segmentation with multimodal transformers

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.525487Z

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Observation a73c0f97-4901-4b21-9430-ed6862033505 · outbound

This paper cites Language as queries for referring video object segmentation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Language as queries for referring video object segmentation

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.529070Z

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Observation a8aefe18-3392-453b-af81-59955c90c254 · outbound

This paper cites OnlineRefer: A simple online baseline for referring video object segmentation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking OnlineRefer: A simple online baseline for referring video object segmentation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.533130Z

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Observation 837bb708-c099-49b8-b8ea-34c0fd495a9c · outbound

This paper cites Referred by multi-modality: A unified temporal transformer for video object segmentation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Referred by multi-modality: A unified temporal transformer for video object segmentation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.536682Z

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Observation c9ac700a-964c-4345-a224-2eb062770649 · outbound

This paper cites ReferDINO: Referring video object segmentation with visual grounding foundations.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking ReferDINO: Referring video object segmentation with visual grounding foundations

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.540171Z

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Observation a6f77647-25b1-4f4d-85df-8a5ecb326382 · outbound

This paper cites an unresolved cited work.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Unresolved cited work

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Observation 489213f2-5b8d-4503-99c5-8dd07081ce2b · outbound

This paper cites Domain-adversarial training of neural networks.Journal of Machine Learning Research, 17(59):1–35, 2016.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Domain-adversarial training of neural networks.Journal of Machine Learning Research, 17(59):1–35, 2016

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.548406Z

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Observation ac3f627b-0031-4ea3-a92e-bed655cac067 · outbound

This paper cites Adversarial discriminative domain adaptation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Adversarial discriminative domain adaptation

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Observation d6fc01ff-b350-43dd-9ec6-b86c34406672 · outbound

This paper cites an unresolved cited work.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Unresolved cited work

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Observation fa7094ef-15fc-491f-837d-176cee8e3247 · outbound

This paper cites Maximum classifier discrepancy for unsupervised domain adaptation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Maximum classifier discrepancy for unsupervised domain adaptation

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Observation 45a20581-d35d-44a0-b1d6-a73a3d05eb9b · outbound

This paper cites Domain adaptive Faster R-CNN for object detection in the wild.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Domain adaptive Faster R-CNN for object detection in the wild

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Observation 36fcde95-1114-40e3-9917-85d0dd8076e9 · outbound

This paper cites Strong-weak distribution alignment for adaptive object detection.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Strong-weak distribution alignment for adaptive object detection

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Observation 852704f9-1462-4513-86f7-28f69f8ef866 · outbound

This paper cites Exploring object relation in mean teacher for cross-domain detection.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Exploring object relation in mean teacher for cross-domain detection

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Observation bd09fe01-9b6f-4af2-be3d-555136220abe · outbound

This paper cites Unbiased mean teacher for cross-domain object detection.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Unbiased mean teacher for cross-domain object detection

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Observation 8a7f8786-c624-4c40-89dd-089999d08ac0 · outbound

This paper cites Cross-domain adaptive teacher for object detection.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Cross-domain adaptive teacher for object detection

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Observation 11ebed19-386e-45b3-a9f1-351357cce812 · outbound

This paper cites Learning domain adaptive object detection with probabilistic teacher.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Learning domain adaptive object detection with probabilistic teacher

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Observation d70a8588-735a-4486-9a7b-66acc7707bf7 · outbound

This paper cites UPRE: Zero- shot domain adaptation for object detection via unified prompt and representation enhancement.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking UPRE: Zero- shot domain adaptation for object detection via unified prompt and representation enhancement

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Observation 0dfa03c5-8246-4cfa-aa0d-9a0c34a8e57d · outbound

This paper cites Temporal attentive alignment for large-scale video domain adaptation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Temporal attentive alignment for large-scale video domain adaptation

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Observation 5194a337-8ea6-4ceb-889a-617f8860bf09 · outbound

This paper cites Tent: Fully test-time adaptation by entropy minimization.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Tent: Fully test-time adaptation by entropy minimization

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Observation 77143bad-a669-4621-9565-d5e431a28671 · outbound

This paper cites Continual test-time domain adaptation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Continual test-time domain adaptation

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Observation d08d9834-f438-4ab2-b407-3b660129ac1a · outbound

This paper cites Efficient test-time model adaptation without forgetting.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Efficient test-time model adaptation without forgetting

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Observation ea662b2b-183e-4b96-8100-12facf88a99a · outbound

This paper cites A probabilistic framework for lifelong test-time adaptation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking A probabilistic framework for lifelong test-time adaptation

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Observation 405b536d-f486-4475-85c4-2a825313d817 · outbound

This paper cites Synthetic- to-real video person Re-ID.IEEE Transactions on Information F orensics and Security, 20: 5438–5450, 2025.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Synthetic- to-real video person Re-ID.IEEE Transactions on Information F orensics and Security, 20: 5438–5450, 2025

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Observation c239d814-93dc-4a90-bfa8-fd4c13774b1d · outbound

This paper cites A new bench- mark and algorithm for clothes-changing video person re-identification.IEEE Transactions on Information F orensics and Security, 20:1993–2005, 2025.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking A new bench- mark and algorithm for clothes-changing video person re-identification.IEEE Transactions on Information F orensics and Security, 20:1993–2005, 2025

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Observation 53334a74-2a56-46c1-8a57-2cdd15b1e599 · outbound

This paper cites Are we ready for autonomous driving? the KITTI vision benchmark suite.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Are we ready for autonomous driving? the KITTI vision benchmark suite

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Observation 2fdbbce0-cb89-4509-89ac-d06ae3d26dec · outbound

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

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking MOT16: A Benchmark for Multi-Object Tracking

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Observation 34ab5c3a-e5c1-4a1d-8ddf-e4009503f9f7 · outbound

This paper cites The Cityscapes dataset for semantic urban scene understanding.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking The Cityscapes dataset for semantic urban scene understanding

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Observation f8c26306-d780-41dd-b87d-da99a2214da2 · outbound

This paper cites BDD100K: A diverse driving dataset for heterogeneous multitask learning.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking BDD100K: A diverse driving dataset for heterogeneous multitask learning

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Observation f50c48d1-aba5-42e9-8c45-5b204cb572e3 · outbound

This paper cites Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Lang, Sourabh V ora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.629072Z

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Observation d6392c46-7303-41c9-853e-2a1007e2ccd3 · outbound

This paper cites Virtual worlds as proxy for multi-object tracking analysis.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Virtual worlds as proxy for multi-object tracking analysis

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.632542Z

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Observation 9dc284e3-c27b-4189-ac2a-7ba08dbecf99 · outbound

This paper cites Virtual KITTI 2.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Virtual KITTI 2

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.636252Z

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Observation 04296b7f-bb4d-4e46-95a3-48c597d4df29 · outbound

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CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Unresolved cited work

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.640180Z

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Observation b2de5920-231e-46c1-867f-4859c3f70360 · outbound

This paper cites Richter, Vibhav Vineet, Stefan Roth, and Vladlen Koltun.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Richter, Vibhav Vineet, Stefan Roth, and Vladlen Koltun

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.643873Z

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Observation ed4eeffb-c6ab-476d-99ab-0af602dfeebe · outbound

This paper cites SHIFT: A synthetic driving dataset for continuous multi-task domain adaptation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking SHIFT: A synthetic driving dataset for continuous multi-task domain adaptation

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.647271Z

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Observation 3efe9f73-2f12-48ee-8022-38d3841cc1cb · outbound

This paper cites VisDA: The Visual Domain Adaptation Challenge.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking VisDA: The Visual Domain Adaptation Challenge

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.650852Z

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Observation 0ed24bf0-b131-4d66-993f-ebe74565f88e · outbound

This paper cites Moment matching for multi-source domain adaptation.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking Moment matching for multi-source domain adaptation

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Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:45.654680Z

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This paper cites WILDS: A benchmark of in-the-wild distribution shifts.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking WILDS: A benchmark of in-the-wild distribution shifts

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Observation db54c083-9e5f-46c6-ad34-602b4fd41412 · outbound

This paper cites AerialMind: Towards referring multi-object tracking in UA V scenarios.

CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking AerialMind: Towards referring multi-object tracking in UA V scenarios

Reference 59

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