Paper Citation Record · LEDGER

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation

As of 20 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 3 inbound Pith citation observations for arXiv:2411.18229.

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

pith.paper-citation-record.v1
2411.18229 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:28:36.356789Z

measured 60 of 60 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:36:13.658546Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T20:52:02.779076Z

Reference resolution

57 of 57 outbound references displayed

verified exact0
verified fuzzy39
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f2fd680b-66cf-40c0-8fe0-6d427c6e8d5a · outbound

This paper cites ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data

Reference 1

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Observation 4b463d5d-c837-4ecd-9e98-0ab7a6c0f2b7 · outbound

This paper cites Zoedepth: Zero-shot transfer by com- bining relative and metric depth, 2023.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Zoedepth: Zero-shot transfer by com- bining relative and metric depth, 2023

Reference 2

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Observation 3a17eaa2-6513-48b3-9194-62a9b0a92c3c · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation nuscenes: A multi- modal dataset for autonomous driving

Reference 3

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Observation e357436a-6bcd-4fa8-b973-5138f1369027 · outbound

This paper cites Oasis: A large-scale dataset for single image 3d in the wild.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Oasis: A large-scale dataset for single image 3d in the wild

Reference 4

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Observation 17f60c4b-a2ba-47ba-bd93-481e48614879 · outbound

This paper cites Indoor scene understanding with geometric and semantic contexts.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Indoor scene understanding with geometric and semantic contexts

Reference 5

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Observation e71029a1-24b7-4b9e-b80c-1240d497eee3 · outbound

This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Scannet: Richly-annotated 3d reconstructions of indoor scenes

Reference 6

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Observation d00b724b-04aa-49c8-8938-8534fb9f2a80 · outbound

This paper cites Towards real-time monocular depth estimation for robotics: A survey.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Towards real-time monocular depth estimation for robotics: A survey

Reference 7

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Observation 80eb96c4-49b2-4e90-8f3f-56495043cc85 · outbound

This paper cites Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3d scans.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Omnidata: A scalable pipeline for making multi-task mid-level vision datasets from 3d scans

Reference 8

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Observation 62c7bdbe-2003-4baa-bb18-bcbe3490c34c · outbound

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

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Depth map prediction from a single image using a multi-scale deep net- work

Reference 9

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Observation ddc92865-c98a-4060-a193-8335e214a54f · outbound

This paper cites Deep ordinal regression net- work for monocular depth estimation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Deep ordinal regression net- work for monocular depth estimation

Reference 10

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Observation 57bd3243-055e-432a-8264-8090b5c1b9aa · outbound

This paper cites Geowiz- ard: Unleashing the diffusion priors for 3d geometry estima- tion from a single image.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Geowiz- ard: Unleashing the diffusion priors for 3d geometry estima- tion from a single image

Reference 11

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Observation c5431b83-0b54-4dd4-8284-e3680ac4051c · outbound

This paper cites Vision meets robotics: The kitti dataset.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Vision meets robotics: The kitti dataset

Reference 12

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Observation adbdadb0-21f1-4779-bd06-49f15e57bd20 · outbound

This paper cites Digging into self-supervised monocular depth estimation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Digging into self-supervised monocular depth estimation

Reference 13

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Observation 6d7baf6c-7eca-42ef-a789-b601c2007a34 · outbound

This paper cites 3d packing for self-supervised monocular depth estimation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation 3d packing for self-supervised monocular depth estimation

Reference 14

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Observation 4bec643b-be73-414d-b1f8-c00cc62b2389 · outbound

This paper cites Full surround mon- odepth from multiple cameras.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Full surround mon- odepth from multiple cameras

Reference 15

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Observation 3ef54728-1834-444e-bc35-a064a9cfeb1d · outbound

This paper cites Towards zero-shot scale-aware monoc- ular depth estimation, 2023.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Towards zero-shot scale-aware monoc- ular depth estimation, 2023

Reference 16

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Observation 836fb508-6a0d-4ff3-8a7f-c24e733bc8cb · outbound

This paper cites Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

Reference 17

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Observation dbe62cee-5043-47a4-b8be-cf8bbd2a66ad · outbound

This paper cites Denoising diffu- sion probabilistic models.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Denoising diffu- sion probabilistic models

Reference 18

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Observation c2cfaa5c-a049-44b6-8777-872eb4d9dfbc · outbound

This paper cites Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Metric3Dv2: A Versatile Monocular Geometric Foundation Model for Zero-shot Metric Depth and Surface Normal Estimation

Reference 19

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Observation 68282613-bce8-4e49-b5ec-17b30dfba08e · outbound

This paper cites BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusion

Reference 20

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Observation 7e90c85f-3bb4-41c7-aec4-92a9254037f6 · outbound

This paper cites Repurpos- ing diffusion-based image generators for monocular depth estimation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Repurpos- ing diffusion-based image generators for monocular depth estimation

Reference 21

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Observation 2a38a7bd-2c2c-4cbb-8c5f-9ee4e99abc30 · outbound

This paper cites Evaluation of cnn-based single-image depth estimation methods.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Evaluation of cnn-based single-image depth estimation methods

Reference 22

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Observation 7d83c583-9541-4a65-92cf-f04d5e74b178 · outbound

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

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation

Reference 23

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Observation beee60e7-95e9-4133-99fe-1572986beece · outbound

This paper cites Megadepth: Learning single- view depth prediction from internet photos.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Megadepth: Learning single- view depth prediction from internet photos

Reference 24

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Observation 1ceeefa7-d65d-4be1-8b66-cb1e78aba426 · outbound

This paper cites Patchre- finer: Leveraging synthetic data for real-domain high- resolution monocular metric depth estimation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Patchre- finer: Leveraging synthetic data for real-domain high- resolution monocular metric depth estimation

Reference 25

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Observation ddec51ea-f85c-44ee-843a-8c24aeb4c450 · outbound

This paper cites Magic3d: High-resolution text-to-3d content creation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Magic3d: High-resolution text-to-3d content creation

Reference 26

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Observation ada5a198-2515-4890-b416-0db38d167673 · outbound

This paper cites Repaint: Inpainting using denoising diffusion probabilistic models.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Repaint: Inpainting using denoising diffusion probabilistic models

Reference 27

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Observation 0f4e2c35-be61-410d-a579-a4bf02748b1a · outbound

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SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Unresolved cited work

Reference 28

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Observation 49008777-0c1b-44f8-b086-91525ecacc37 · outbound

This paper cites Spring: A high-resolution high- detail dataset and benchmark for scene flow, optical flow and stereo.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Spring: A high-resolution high- detail dataset and benchmark for scene flow, optical flow and stereo

Reference 29

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Observation fdee4feb-1ac3-464f-a76b-5fcbf4e7f752 · outbound

This paper cites Swiftbrush: One-step text-to-image diffusion model with variational score distilla- tion.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Swiftbrush: One-step text-to-image diffusion model with variational score distilla- tion

Reference 30

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Observation bbfbfba9-8934-4b19-9483-38103e2dc0bf · outbound

This paper cites UniDepth: Universal monocular metric depth estimation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation UniDepth: Universal monocular metric depth estimation

Reference 31

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Observation df20e40b-d8d0-4047-98ad-2eb4e01d0d56 · outbound

This paper cites Barron, and Ben Milden- hall.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Barron, and Ben Milden- hall

Reference 32

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Observation 64f8e8c3-b7e2-43b2-8abf-8b6b58a4a4d3 · outbound

This paper cites Booster: a benchmark for depth from images of specular and transparent surfaces.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Booster: a benchmark for depth from images of specular and transparent surfaces

Reference 33

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Observation 2389df92-a356-4639-bfd1-dfa128e0c4f6 · outbound

This paper cites Vi- sion transformers for dense prediction.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Vi- sion transformers for dense prediction

Reference 34

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Observation c5adfc1a-2284-4ea9-884e-4ac69c50ead8 · outbound

This paper cites Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer

Reference 35

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Observation f2051dd1-f961-438d-857b-8d60ca389232 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models, 2021.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation High-resolution image syn- thesis with latent diffusion models, 2021

Reference 36

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Observation 8ec66e6d-8adb-42d8-ade8-8916172e379d · outbound

This paper cites A multi-view stereo benchmark with high- resolution images and multi-camera videos.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation A multi-view stereo benchmark with high- resolution images and multi-camera videos

Reference 37

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Observation 8dae800e-ce4d-45f6-88e4-4a591109a143 · outbound

This paper cites Indoor segmentation and support inference from rgbd images.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Indoor segmentation and support inference from rgbd images

Reference 38

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Observation 967c1182-bea5-4d65-a03b-103b212eb589 · outbound

This paper cites A benchmark for the evalua- tion of rgb-d slam systems.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation A benchmark for the evalua- tion of rgb-d slam systems

Reference 39

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Observation f6c02999-db18-4a34-9948-a8a9a35ef843 · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Scalability in perception for autonomous driving: Waymo open dataset

Reference 40

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This paper cites Smd-nets: Stereo mixture density networks.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Smd-nets: Stereo mixture density networks

Reference 41

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Observation 4f21ab82-cc1b-45b3-80d3-4c90c6d4f759 · outbound

This paper cites DIODE: A Dense Indoor and Outdoor DEpth Dataset.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation DIODE: A Dense Indoor and Outdoor DEpth Dataset

Reference 42

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Observation 14a808eb-0751-4d42-b78d-0d2a31c68a8b · outbound

This paper cites Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation

Reference 43

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Observation a1c2650d-3d51-4915-9278-8c4be3a0c3e5 · outbound

This paper cites Can scale-consistent monocu- lar depth be learned in a self-supervised scale-invariant man- ner? In ICCV, 2021.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Can scale-consistent monocu- lar depth be learned in a self-supervised scale-invariant man- ner? In ICCV, 2021

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:28:37.059006Z

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Observation 3160b193-f0a5-48cb-9ff3-5e036030097c · outbound

This paper cites Self-supervised monocular depth hints.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Self-supervised monocular depth hints

Reference 45

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Observation 4474401e-c880-4013-9f5a-9a53022e68b4 · outbound

This paper cites Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

Reference 46

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Observation 6cb7f54b-97d5-4677-b0b1-eb0cdbaf2ff3 · outbound

This paper cites Lessons and insights from creating a syn- thetic optical flow benchmark.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Lessons and insights from creating a syn- thetic optical flow benchmark

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:28:36.910710Z

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Observation 2485ebb7-6ce1-4673-9df7-4a6065c2634f · outbound

This paper cites Pandaset: Advanced sensor suite dataset for autonomous driving.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Pandaset: Advanced sensor suite dataset for autonomous driving

Reference 48

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Observation b19a7c62-4fba-44f9-a2bc-741bc067eb04 · outbound

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

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Depth anything: Unleashing the power of large-scale unlabeled data

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:28:36.881319Z

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Observation f758bb6e-ee00-44f3-942b-b8748540de5e · outbound

This paper cites Virtual normal: En- forcing geometric constraints for accurate and robust depth prediction.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Virtual normal: En- forcing geometric constraints for accurate and robust depth prediction

Reference 50

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Observation d034ab44-2d32-4b5f-b45b-9371ec0123f9 · outbound

This paper cites Metric3d: Towards zero-shot metric 3d prediction from a single image.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Metric3d: Towards zero-shot metric 3d prediction from a single image

Reference 51

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Observation edd14697-3a37-4fa0-9840-5fb32b8dcd66 · outbound

This paper cites Real-time monocular depth estima- tion with sparse supervision on mobile.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Real-time monocular depth estima- tion with sparse supervision on mobile

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:28:36.739541Z

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Observation 8c743229-a495-4a74-95ad-94d2a82f922f · outbound

This paper cites Taskonomy: Disentangling task transfer learning.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Taskonomy: Disentangling task transfer learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:28:36.724355Z

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Observation 51ec09bd-8aae-41c0-9202-d3a51d436e36 · outbound

This paper cites 3dmatch: Learning local geometric descriptors from rgb-d reconstruc- tions.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation 3dmatch: Learning local geometric descriptors from rgb-d reconstruc- tions

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:28:36.692193Z

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Observation 8e6f9a3a-ff5d-4c58-bea6-73d2dd92fa0c · outbound

This paper cites BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation BetterDepth: Plug-and-Play Diffusion Refiner for Zero-Shot Monocular Depth Estimation

Reference 55

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Observation be93b98f-9fd0-418f-a84f-7dd0700aacf9 · outbound

This paper cites Tryondiffusion: A tale of two un- ets.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Tryondiffusion: A tale of two un- ets

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:28:36.639338Z

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Observation 56ba7e0e-1980-4ac6-b493-1fa8489f9781 · outbound

This paper cites an unresolved cited work.

SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation Unresolved cited work

Reference 2024

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Pith citing papers

Observation 849fc714-5819-4b94-ac0c-3e2b48db6500 · inbound

E3D-Bench: A Benchmark for End-to-End 3D Geometric Foundation Models cites this paper.

E3D-Bench: A Benchmark for End-to-End 3D Geometric Foundation Models SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation

Reference 117

Resolution: unresolved; no resolver link, observed 2026-08-07T11:36:13.658546Z

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Observation c39f6727-c0a0-4340-87d7-a4d9745b4948 · inbound

MetricHMSR:Metric Human Mesh and Scene Recovery from Monocular Images cites this paper.

MetricHMSR:Metric Human Mesh and Scene Recovery from Monocular Images SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation

Reference 37

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Observation 9dccec04-3022-411c-8bff-a3e9e7efde5d · inbound

Depth Anything at Any Condition cites this paper.

Depth Anything at Any Condition SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation

Reference 56

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