Paper Citation Record · LEDGER

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations

As of 15 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2507.00981.

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

pith.paper-citation-record.v1
2507.00981 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:07:15.240988Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:55:22.492421Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T10:01:28.842415Z

Reference resolution

47 of 47 outbound references displayed

verified exact0
verified fuzzy21
unresolved24
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f14ea066-dc93-4271-9f08-ac7a76e221f2 · outbound

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

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:15.046659Z

Source-reported events for the cited work

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Observation d95c2362-26e4-49b0-a8b7-ca5205e68b6c · outbound

This paper cites MiDaS v3.1 -- A Model Zoo for Robust Monocular Relative Depth Estimation.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations MiDaS v3.1 -- A Model Zoo for Robust Monocular Relative Depth Estimation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:15.051566Z

Source-reported events for the cited work

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Observation 229e7cd2-29bf-4023-bd2a-177d135e9077 · outbound

This paper cites Depth Pro: Sharp Monocular Metric Depth in Less Than a Second.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Depth Pro: Sharp Monocular Metric Depth in Less Than a Second

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:15.056418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0c60328-bdb5-4f96-94ca-1a43739b278c · outbound

This paper cites an unresolved cited work.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Unresolved cited work

Reference 4

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Source-reported events for the cited work

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Observation 5ee1c9c4-03b0-4878-8f6d-3391c872cd50 · outbound

This paper cites ProcTHOR: Large-Scale Embodied AI Using Procedural Generation.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations ProcTHOR: Large-Scale Embodied AI Using Procedural Generation

Reference 5

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Source-reported events for the cited work

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Observation 9e64bfeb-4fa9-47db-bc94-c9435f62bed5 · outbound

This paper cites Meta-sim2: Unsupervised learning of scene structure for synthetic data generation.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Meta-sim2: Unsupervised learning of scene structure for synthetic data generation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.922070Z

Source-reported events for the cited work

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Observation ef061606-1fea-4af5-b687-b61cbe26dadd · outbound

This paper cites 3d-front: 3d furnished rooms with layouts and semantics.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations 3d-front: 3d furnished rooms with layouts and semantics

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.908292Z

Source-reported events for the cited work

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Observation ee463007-42e4-4216-9e93-2c98af29fea4 · outbound

This paper cites Adversarial Robustness for Visual Grounding of Multimodal Large Language Models.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Adversarial Robustness for Visual Grounding of Multimodal Large Language Models

Reference 8

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Source-reported events for the cited work

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Observation 425c9c3f-feee-42a3-b28a-47755a619f48 · outbound

This paper cites Vision meets robotics: The kitti dataset.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Vision meets robotics: The kitti dataset

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.895051Z

Source-reported events for the cited work

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Observation a5e29e17-4ff3-47d9-a60d-c1aef5ee3769 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Explaining and Harnessing Adversarial Examples

Reference 10

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Source-reported events for the cited work

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Observation 5ebfb37e-e48b-4920-a55a-9fab25ebccb3 · outbound

This paper cites Evaluating concurrent robust- ness of language models across diverse challenge sets.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Evaluating concurrent robust- ness of language models across diverse challenge sets

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.881473Z

Source-reported events for the cited work

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Observation d9f3ff9d-cf9b-41c8-a530-032d0ef1e176 · outbound

This paper cites Natural adversarial examples.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Natural adversarial examples

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.866349Z

Source-reported events for the cited work

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Observation 0d93ea7f-20a8-4464-9f1a-7e17456057f7 · outbound

This paper cites Xiaoyan Zhang, Zhipeng Cai, Xiaoxiao Long, Hao Chen, Kaixuan Wang, Gang Yu, Chunhua Shen, and Shaojie Shen.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Xiaoyan Zhang, Zhipeng Cai, Xiaoxiao Long, Hao Chen, Kaixuan Wang, Gang Yu, Chunhua Shen, and Shaojie Shen

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.853093Z

Source-reported events for the cited work

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Observation 6e762e25-43f1-4cc2-a98b-3d04fa9aac99 · outbound

This paper cites Champion-level drone racing using deep reinforcement learning.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Champion-level drone racing using deep reinforcement learning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.839609Z

Source-reported events for the cited work

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Observation d5548e9d-3795-4d0d-a744-51f1b83efb0e · outbound

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

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Repurposing diffusion-based image generators for monocular depth estimation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.813500Z

Source-reported events for the cited work

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Observation bc726707-6d4a-4c81-a914-4d5355a3bef9 · outbound

This paper cites Czarnecki.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Czarnecki

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.800222Z

Source-reported events for the cited work

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Observation ae66f947-73c0-4224-928a-b5485510fc8b · outbound

This paper cites RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions

Reference 17

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Source-reported events for the cited work

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Observation 508cf113-b22c-48f7-9154-046f73ad0518 · outbound

This paper cites Adversarial examples in the physical world.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Adversarial examples in the physical world

Reference 18

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Source-reported events for the cited work

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Observation 2ff9a188-08e6-4dc9-888d-99dc42974aef · outbound

This paper cites Pulling things out of perspective.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Pulling things out of perspective

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.787358Z

Source-reported events for the cited work

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Observation 01938272-cc63-47d0-a8e9-63549ecf4ff1 · outbound

This paper cites Learning quadrupedal locomotion over challenging terrain.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Learning quadrupedal locomotion over challenging terrain

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.774239Z

Source-reported events for the cited work

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Observation 99662906-7507-4eac-96f4-472dc6dc2819 · outbound

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

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Spring: A high- resolution high-detail dataset and benchmark for scene flow, optical flow and stereo

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.760561Z

Source-reported events for the cited work

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Observation e0de7f4b-7ccd-4395-ae76-20c1892a05a6 · outbound

This paper cites Unidepth: Universal monocular metric depth estimation.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Unidepth: Universal monocular metric depth estimation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.746389Z

Source-reported events for the cited work

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Observation 78b53694-1e56-4d04-b0f4-7821be16229d · outbound

This paper cites UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler

Reference 23

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Source-reported events for the cited work

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Observation abe427c6-ea2c-4c7e-890f-620c19596a4d · outbound

This paper cites Visual adversarial examples jailbreak aligned large language models.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Visual adversarial examples jailbreak aligned large language models

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.732025Z

Source-reported events for the cited work

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Observation 4c9ad9e8-9d21-409e-8296-988b8be77ade · outbound

This paper cites an unresolved cited work.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Unresolved cited work

Reference 25

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Source-reported events for the cited work

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Observation 206fabc6-aceb-4658-9a4b-6179f10fb16f · outbound

This paper cites an unresolved cited work.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Unresolved cited work

Reference 26

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Observation 43612749-da58-4842-88a0-0cca07580e6c · outbound

This paper cites Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer

Reference 27

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Observation 8e451d8e-611c-4478-8206-800ae0210708 · outbound

This paper cites Hypersim: A photorealistic synthetic dataset for holistic indoor scene understanding.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Hypersim: A photorealistic synthetic dataset for holistic indoor scene understanding

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.690428Z

Source-reported events for the cited work

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Observation 50edd43b-57c9-4a3e-8efe-d333cdb7dea3 · outbound

This paper cites Make3d: Learning 3d scene structure from a single still image.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Make3d: Learning 3d scene structure from a single still image

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.662843Z

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Observation ee89a456-cdf5-4390-b6ce-9ab87986cd74 · outbound

This paper cites Schönberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and Andreas Geiger.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Schönberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and Andreas Geiger

Reference 30

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Observation c99ccccc-7911-4d5e-b8bf-5861586e8a26 · outbound

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

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Indoor segmentation and support inference from rgbd images

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.632203Z

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Observation bd0eba52-5c8e-4996-a24e-528c4ce92e4d · outbound

This paper cites Intriguing properties of neural networks.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Intriguing properties of neural networks

Reference 32

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Source-reported events for the cited work

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Observation 4cd5625a-e011-486e-93b9-23305fb361e0 · outbound

This paper cites Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.618033Z

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Observation e4a6f3d5-a628-4e36-937b-869e8889d635 · outbound

This paper cites Deep Patch Visual Odometry.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Deep Patch Visual Odometry

Reference 34

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Observation d6ba0edc-08dd-413e-8d3e-5e37baa61e3c · outbound

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

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations DIODE: A Dense Indoor and Outdoor DEpth Dataset

Reference 35

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Observation ed3a0578-3a27-4391-99aa-c780ddb2ca01 · outbound

This paper cites InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective

Reference 36

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Observation fc9f0b3b-194d-4e02-932d-47bbb20ff156 · outbound

This paper cites Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models

Reference 37

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Observation f4a1f8df-2cb6-4039-aaca-e05672acfd7e · outbound

This paper cites MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T21:07:15.214581Z

Source-reported events for the cited work

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Observation c2f18094-9db5-4bf7-b41d-f650bdf65fb1 · outbound

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Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Unresolved cited work

Reference 39

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Observation ce1c65df-de18-4fb8-84c7-d73bf4df0c71 · outbound

This paper cites Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing

Reference 40

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Source-reported events for the cited work

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Observation f5195f61-e4ef-4eff-8864-30391037c3d7 · outbound

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

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Depth anything: Unleashing the power of large-scale unlabeled data

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.587993Z

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Observation 6261b1d8-b9db-4cee-bec3-adee9255d4d5 · outbound

This paper cites Depth Anything V2.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Depth Anything V2

Reference 42

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Source-reported events for the cited work

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Observation 013d493f-a0e9-4234-9b22-adea8b518591 · outbound

This paper cites Holodeck: Language guided generation of 3d embodied ai environments.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Holodeck: Language guided generation of 3d embodied ai environments

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:07:15.573778Z

Source-reported events for the cited work

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Observation 0038e15b-b7a1-4c4b-aaf9-f509da3a0e09 · outbound

This paper cites On Evaluating Adversarial Robustness of Large Vision-Language Models.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations On Evaluating Adversarial Robustness of Large Vision-Language Models

Reference 44

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Observation 2851a609-4878-4423-9435-ddc3639e5d2a · outbound

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Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Unresolved cited work

Reference 2020

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Observation 921ab67b-f201-471a-b2c6-21c8e746ebd2 · outbound

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Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Unresolved cited work

Reference 2023

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Observation 61f48b58-e999-4a73-a3cb-07fab3ff21b3 · outbound

This paper cites an unresolved cited work.

Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations Unresolved cited work

Reference 2024

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Source-reported events for the cited work

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Pith citing papers

Observation d3d7e650-27d9-4f58-aa4e-fe40cace0a3f · inbound

ProcFunc: Function-Oriented Abstractions for Procedural 3D Generation in Python cites this paper.

ProcFunc: Function-Oriented Abstractions for Procedural 3D Generation in Python Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations

Reference 19

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T10:01:28.845051Z

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Observation 1d9fcbf3-0c62-4456-bfb1-8a63a91fa0d9 · inbound

Geometric Distillation from Rectified Stereo: Leveraging Epipolar Cues for Monocular Depth cites this paper.

Geometric Distillation from Rectified Stereo: Leveraging Epipolar Cues for Monocular Depth Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations

Reference 79

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Source-reported events for the cited work

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