Paper Citation Record · LEDGER

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision

As of 18 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2608.11564.

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

pith.paper-citation-record.v1
2608.11564 v1

Coverage vector

measured 42 of 42 reference resolution

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

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External citation measurements

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Outbound references

Observation 4c152bbd-38b2-402e-b112-ea47e7ad0c22 · outbound

This paper cites Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Pseudo-lidar from visual depth estimation: Bridging the gap in 3d object detection for autonomous driving,

Reference 1

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Observation 8f3f0169-fefa-4304-9f99-ab3b38964298 · outbound

This paper cites A framework for 3d object detection and pose estimation in unstructured environment using single shot detector and refined linemod template matching,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision A framework for 3d object detection and pose estimation in unstructured environment using single shot detector and refined linemod template matching,

Reference 2

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Observation 758c3da9-7aba-48e2-a6f9-dbce98e59c59 · outbound

This paper cites Fastdepth: Fast monocular depth estimation on embedded systems,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Fastdepth: Fast monocular depth estimation on embedded systems,

Reference 3

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Observation e73db7d0-6956-4530-90b4-d13e031b55a5 · outbound

This paper cites Real-time 3d object proposal gener- ation and classification using limited processing resources,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Real-time 3d object proposal gener- ation and classification using limited processing resources,

Reference 4

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Observation bebd0cea-84af-4af7-8c8c-81e575e4f7aa · outbound

This paper cites Multiseam tracking with a portable robotic welding system in unstructured environments,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Multiseam tracking with a portable robotic welding system in unstructured environments,

Reference 5

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Observation d5eec219-f4d0-41c0-9989-a8bc5eff601f · outbound

This paper cites Depth map prediction from a single image using a multi-scale deep network,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Depth map prediction from a single image using a multi-scale deep network,

Reference 6

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Observation 4d70bd38-2176-425b-a69c-b4012d24d158 · outbound

This paper cites Adabins: Depth estimation using adaptive bins,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Adabins: Depth estimation using adaptive bins,

Reference 7

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Observation 1211424c-8ce4-4b33-b749-863466e979cc · outbound

This paper cites Depth anything: Unleashing the power of large-scale unlabeled data,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Depth anything: Unleashing the power of large-scale unlabeled data,

Reference 8

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Observation c43a3403-81bd-4b38-8a1e-4f7e5109523d · outbound

This paper cites Deep depth estimation from thermal image,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Deep depth estimation from thermal image,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T00:40:46.110757Z

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Observation 92966767-47a3-4bf3-8ddb-72cde3885a54 · outbound

This paper cites Segment anything,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Segment anything,

Reference 10

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Source-reported events for the cited work

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Observation d75b32c9-de38-4151-8403-559535bb19d6 · outbound

This paper cites DINOv3.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision DINOv3

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T00:40:46.118282Z

Source-reported events for the cited work

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Observation 1fbafcca-3f55-4fca-87db-a20e43760cf0 · outbound

This paper cites Enhancing features in long-tailed data using large vision model,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Enhancing features in long-tailed data using large vision model,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:40:46.629609Z

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Observation 6a1c6dfa-5d72-4cdf-b71a-37c14136ce9c · outbound

This paper cites Emerging properties in self-supervised vision trans- formers,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Emerging properties in self-supervised vision trans- formers,

Reference 13

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Observation 816096fb-5c0b-4cd1-a913-bb3d353f1fc5 · outbound

This paper cites Dinov2: Learning robust visual features without supervision,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Dinov2: Learning robust visual features without supervision,

Reference 14

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Observation 048924f9-0550-488a-aae2-e4963401e5d9 · outbound

This paper cites General- izable thermal-based depth estimation via pre-trained visual foundation model,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision General- izable thermal-based depth estimation via pre-trained visual foundation model,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:40:46.596953Z

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Observation 64e7c6a0-cae5-4426-972c-814d84a74cad · outbound

This paper cites Monother-depth: Enhancing thermal depth estimation via confidence- aware distillation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Monother-depth: Enhancing thermal depth estimation via confidence- aware distillation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:40:46.584218Z

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Observation 4e4be2c5-19ee-4849-bd7e-d1fc03ccc40c · outbound

This paper cites Depth and surface normal estimation from monocular images using regression on deep features and hierarchical crfs,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Depth and surface normal estimation from monocular images using regression on deep features and hierarchical crfs,

Reference 17

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Observation fc00b4b9-7024-4fd4-bb78-cd0edd8fd06c · outbound

This paper cites Enforcing geometric con- straints of virtual normal for depth prediction,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Enforcing geometric con- straints of virtual normal for depth prediction,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:40:46.558424Z

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Observation 544853d4-3d76-4a62-8532-a1915f9311ca · outbound

This paper cites Gedepth: Ground embedding for monocular depth estimation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Gedepth: Ground embedding for monocular depth estimation,

Reference 19

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Observation d8ea3492-026a-4e0d-97c2-35e02a2a2496 · outbound

This paper cites Nddepth: Normal- distance assisted monocular depth estimation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Nddepth: Normal- distance assisted monocular depth estimation,

Reference 20

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Observation 9ccc54df-fd49-4b18-8203-8b6699e358fa · outbound

This paper cites Binsformer: Revisiting adaptive bins for monocular depth estimation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Binsformer: Revisiting adaptive bins for monocular depth estimation,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:40:46.519150Z

Source-reported events for the cited work

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Observation f780f845-321f-4f83-9f1b-a2558e898b29 · outbound

This paper cites Structure- guided ranking loss for single image depth prediction,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Structure- guided ranking loss for single image depth prediction,

Reference 22

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Observation a3e63a62-b98a-48d4-8a0f-1970846e1630 · outbound

This paper cites Neural window fully- connected crfs for monocular depth estimation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Neural window fully- connected crfs for monocular depth estimation,

Reference 23

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Observation 965247d9-86db-47c5-9b61-2426da7b9ee4 · outbound

This paper cites Repurposing diffusion-based image generators for monocular depth estimation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Repurposing diffusion-based image generators for monocular depth estimation,

Reference 24

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Observation ce7c1c4e-690f-4660-89e4-1b24018a3f25 · outbound

This paper cites Depth anything v2,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Depth anything v2,

Reference 25

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Observation 14a36a47-9a02-4563-b4d2-7f0eabb4cef5 · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision High-resolution image synthesis with latent diffusion models,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T00:40:46.177361Z

Source-reported events for the cited work

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Observation 3a9e77f8-cfa9-4e36-9657-4d4679fa2408 · outbound

This paper cites Multispectral transfer network: Unsupervised depth estimation for all-day vision,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Multispectral transfer network: Unsupervised depth estimation for all-day vision,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:40:46.462923Z

Source-reported events for the cited work

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Observation 665b9be1-eeed-4464-91e5-d15694deaa4a · outbound

This paper cites An alternative of lidar in nighttime: Unsupervised depth estimation based on single thermal image,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision An alternative of lidar in nighttime: Unsupervised depth estimation based on single thermal image,

Reference 28

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Observation 956f29a6-c828-423c-9276-cd8ca53b15a4 · outbound

This paper cites Self-supervised monocular depth estimation from thermal images via adversarial multi-spectral adaptation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Self-supervised monocular depth estimation from thermal images via adversarial multi-spectral adaptation,

Reference 29

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Observation ffea1512-60f6-4d7a-bbc2-82233c412500 · outbound

This paper cites Thermostereort: Thermal stereo matching in real time via knowledge distillation and attention-based refinement,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Thermostereort: Thermal stereo matching in real time via knowledge distillation and attention-based refinement,

Reference 30

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Observation 8484ebf5-4e20-4d17-ac06-8625055517aa · outbound

This paper cites Abm- drnet: Adaptive-weighted bi-directional modality difference reduction network for rgb-t semantic segmentation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Abm- drnet: Adaptive-weighted bi-directional modality difference reduction network for rgb-t semantic segmentation,

Reference 31

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Observation b34ca6ea-05da-44fe-9c67-397f9824db67 · outbound

This paper cites Efficient rgb- t tracking via cross-modality distillation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Efficient rgb- t tracking via cross-modality distillation,

Reference 32

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Observation 31d4235a-197e-44ec-847e-05e52cd75561 · outbound

This paper cites Efficient and accurate object detection with simultaneous classification and tracking under limited computing power,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Efficient and accurate object detection with simultaneous classification and tracking under limited computing power,

Reference 33

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Observation fc01afe2-06c2-4c22-b5f4-c795ea3a2c2b · outbound

This paper cites D3t: Distinctive dual-domain teacher zigzagging across rgb-thermal gap for domain-adaptive object detection,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision D3t: Distinctive dual-domain teacher zigzagging across rgb-thermal gap for domain-adaptive object detection,

Reference 34

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Observation e6a70e94-277e-4702-a0b6-6cb8c5f492cd · outbound

This paper cites M-specgene: Generalized foundation model for rgbt multispectral vision,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision M-specgene: Generalized foundation model for rgbt multispectral vision,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:40:46.363883Z

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Observation 5d691ee0-e41d-4c77-bc21-41f1199b16e7 · outbound

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

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Swin transformer: Hierarchical vision transformer using shifted windows,

Reference 36

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Observation 5c12eae7-7bc1-4163-829c-2db7d58d9f9d · outbound

This paper cites Deep ordinal regression network for monocular depth estimation,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Deep ordinal regression network for monocular depth estimation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T00:40:46.340561Z

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Observation e5dab7b1-c478-42b7-8954-3b857663d00e · outbound

This paper cites From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation

Reference 38

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Observation d3b87230-5f03-443f-8185-3d9507f0936a · outbound

This paper cites ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

Reference 39

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This paper cites Decoupled weight decay regularization,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Decoupled weight decay regularization,

Reference 40

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Observation 9a0a7092-e505-425c-96e3-4f500bbdc6d7 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Pytorch: An imperative style, high-performance deep learning library,

Reference 41

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Source-reported events for the cited work

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Observation acfec7fe-f70b-4d4d-8650-6c409b6a4311 · outbound

This paper cites Deep Depth Estimation from Thermal Image: Dataset, Benchmark, and Challenges.

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision Deep Depth Estimation from Thermal Image: Dataset, Benchmark, and Challenges

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-16T00:40:46.280304Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

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