The Midas Touch for Metric Depth | Paper Citation Record

Observation 35e8b572-d150-45f9-ab78-df813e29125e · outbound

This paper cites SLIC Superpixels Compared to State-of-the-Art Superpixel Methods.IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(11):2274– 2282.

The Midas Touch for Metric Depth SLIC Superpixels Compared to State-of-the-Art Superpixel Methods.IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(11):2274– 2282

Reference 1

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Observation 1418b8c4-5468-4b17-a7b1-3ec8239d19e6 · outbound

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

The Midas Touch for Metric Depth MiDaS v3.1 -- A Model Zoo for Robust Monocular Relative Depth Estimation

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T01:37:03.266932Z

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Observation bd891219-1368-4a1d-b4c5-0cb39db45235 · outbound

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

The Midas Touch for Metric Depth Depth Pro: Sharp Monocular Metric Depth in Less Than a Second

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:45:15.979924Z

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Observation 22dd0f33-1260-4b3c-b29a-08e9ec9b1a52 · outbound

This paper cites Virtual KITTI 2.

The Midas Touch for Metric Depth Virtual KITTI 2

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-13T16:00:33.810478Z

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Observation 4e673ea6-2ff5-424b-b9c8-f0b1801352c7 · outbound

This paper cites nuScenes: A Multimodal Dataset for Autonomous Driving.

The Midas Touch for Metric Depth nuScenes: A Multimodal Dataset for Autonomous Driving

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.611563Z

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Observation b7624189-229f-431c-9839-20260e0e5ec1 · outbound

This paper cites Domain Generalized Stereo Matching via Hierarchical Visual Transformation.

The Midas Touch for Metric Depth Domain Generalized Stereo Matching via Hierarchical Visual Transformation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.626929Z

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Observation 6c3cfd2b-00fb-4758-b159-40d073321f65 · outbound

This paper cites Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network.

The Midas Touch for Metric Depth Depth Estimation via Affinity Learned with Convolutional Spatial Propagation Network

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.598451Z

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Observation a368fa51-3b18-464a-9e2d-6a15a1754f2f · outbound

This paper cites ScanNet: Richly-Annotated 3D Recon- structions of Indoor Scenes.

The Midas Touch for Metric Depth ScanNet: Richly-Annotated 3D Recon- structions of Indoor Scenes

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.590197Z

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Observation bbe52ff1-3dd4-409c-844e-dc1373525593 · outbound

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

The Midas Touch for Metric Depth Omnidata: A scalable pipeline for mak- ing multi-task mid-level vision datasets from 3d scans

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.602884Z

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Observation a1713ee9-fdae-4dc8-a0b3-77c07716b2fd · outbound

This paper cites Depth map prediction from a single im- age using a multi-scale deep network.Advances in neural information processing systems (NeurIPS), 27.

The Midas Touch for Metric Depth Depth map prediction from a single im- age using a multi-scale deep network.Advances in neural information processing systems (NeurIPS), 27

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.619695Z

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Observation 7415d037-4e70-4cbe-9eb4-3d8725bf1914 · outbound

This paper cites Efficient graph-based image segmentation.International Journal of Computer Vision, 59(2):167–181.

The Midas Touch for Metric Depth Efficient graph-based image segmentation.International Journal of Computer Vision, 59(2):167–181

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.606810Z

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Observation 3887d32d-80db-4747-9080-2a84c7b6609f · outbound

This paper cites ViPOcc: leveraging visual priors from vision foundation models for single-view 3d occupancy prediction.

The Midas Touch for Metric Depth ViPOcc: leveraging visual priors from vision foundation models for single-view 3d occupancy prediction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.580612Z

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Observation 40c144f6-9a3e-488e-8054-f9df64150007 · outbound

This paper cites Geowizard: Unleashing the diffusion priors for 3d geometry estimation from a single image.

The Midas Touch for Metric Depth Geowizard: Unleashing the diffusion priors for 3d geometry estimation from a single image

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.529219Z

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Observation f7e7c17d-b44b-467f-8a7f-884202046c31 · outbound

This paper cites GeoBench: Benchmarking and Analyzing Monocular Geometry Estimation Models.

The Midas Touch for Metric Depth GeoBench: Benchmarking and Analyzing Monocular Geometry Estimation Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:37:03.296896Z

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Observation b038184d-5533-4d33-97c7-baac8b8afd1f · outbound

This paper cites Are we ready for autonomous driv- ing? the KITTI vision benchmark suite.

The Midas Touch for Metric Depth Are we ready for autonomous driv- ing? the KITTI vision benchmark suite

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.544288Z

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Observation abbd0360-32d7-47fe-a7fc-f3f95106978b · outbound

This paper cites Unsupervised Monocular Depth Esti- mation With Left-Right Consistency.

The Midas Touch for Metric Depth Unsupervised Monocular Depth Esti- mation With Left-Right Consistency

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.517181Z

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Observation 462607da-9f2e-4ee6-8388-8ae1b53b8fb1 · outbound

This paper cites Digging Into Self-Supervised Monoc- ular Depth Estimation.

The Midas Touch for Metric Depth Digging Into Self-Supervised Monoc- ular Depth Estimation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.521787Z

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Observation 7426a2e7-e02a-460d-8647-980a126e68f9 · outbound

This paper cites Neural Markov Random Field for Stereo Matching.

The Midas Touch for Metric Depth Neural Markov Random Field for Stereo Matching

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.525031Z

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Observation 32a68cd8-c134-4321-85b1-b1102a6b0e4e · outbound

This paper cites 3D Packing for Self-Supervised Monoc- ular Depth Estimation.

The Midas Touch for Metric Depth 3D Packing for Self-Supervised Monoc- ular Depth Estimation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.553468Z

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Observation 5d512a63-0a03-4fbb-8260-81e1ebcd0fed · outbound

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

The Midas Touch for Metric Depth Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:37:03.314831Z

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Observation 4584bcaf-e6d6-4710-947f-954617204f48 · outbound

This paper cites an unresolved cited work.

The Midas Touch for Metric Depth Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-05-13T14:42:55.512657Z

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Observation fae40862-42f7-4992-a9c8-ce6b01125cd2 · outbound

This paper cites MVSAnywhere: Zero-Shot Multi- View Stereo.

The Midas Touch for Metric Depth MVSAnywhere: Zero-Shot Multi- View Stereo

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.557194Z

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Observation 00c547f8-f02a-49ed-8218-8fde749760dd · outbound

This paper cites Uncertainty Guided Adaptive Warping for Robust and Efficient Stereo Matching.

The Midas Touch for Metric Depth Uncertainty Guided Adaptive Warping for Robust and Efficient Stereo Matching

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.585496Z

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Observation aece6be8-920b-48db-b9e5-4f9db2664b83 · outbound

This paper cites Is my Depth Ground-Truth Good Enough? HAMMER -- Highly Accurate Multi-Modal Dataset for DEnse 3D Scene Regression.

The Midas Touch for Metric Depth Is my Depth Ground-Truth Good Enough? HAMMER -- Highly Accurate Multi-Modal Dataset for DEnse 3D Scene Regression

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:37:03.292046Z

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Observation 41584383-3d11-4025-945a-e216684d0bb5 · outbound

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

The Midas Touch for Metric Depth Repurposing diffusion-based image gen- erators for monocular depth estimation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.492686Z

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Observation 07d00131-12e6-4bca-8d07-fbe6dcc02a72 · outbound

This paper cites Segment Anything.

The Midas Touch for Metric Depth Segment Anything

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.508243Z

Source-reported events for the cited work

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Observation b35a709e-7640-4a74-8cac-276cae3a6c12 · outbound

This paper cites Comparison of monocular depth esti- mation methods using geometrically relevant metrics on the IBims-1 dataset.Computer Vision and Image Understand- ing, 191:102877.

The Midas Touch for Metric Depth Comparison of monocular depth esti- mation methods using geometrically relevant metrics on the IBims-1 dataset.Computer Vision and Image Understand- ing, 191:102877

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.483419Z

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Observation 92e37ff5-e83e-4049-96d9-da4d40b40c81 · outbound

This paper cites Know Your Neighbors: Improving Single- View Reconstruction via Spatial Vision-Language Reason- ing.

The Midas Touch for Metric Depth Know Your Neighbors: Improving Single- View Reconstruction via Spatial Vision-Language Reason- ing

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.479970Z

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Observation 1bab10fe-0108-4a10-837f-6603b5424ee4 · outbound

This paper cites Superpixel Segmenta- tion Using Linear Spectral Clustering.

The Midas Touch for Metric Depth Superpixel Segmenta- tion Using Linear Spectral Clustering

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.471238Z

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Observation 5d242ecf-20e2-4447-a03c-0293762098cd · outbound

This paper cites Distilling Monocular Foundation Model for Fine-grained Depth Completion.

The Midas Touch for Metric Depth Distilling Monocular Foundation Model for Fine-grained Depth Completion

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.462487Z

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Observation 05089d02-2da9-4b68-a12a-f960d93a0c97 · outbound

This paper cites Prompting Depth Anything for 4K Reso- lution Accurate Metric Depth Estimation.

The Midas Touch for Metric Depth Prompting Depth Anything for 4K Reso- lution Accurate Metric Depth Estimation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.457885Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0a1c7e7f-5655-443a-bad6-9f441ff91614 · outbound

This paper cites Dynamic spatial propagation network for depth completion.

The Midas Touch for Metric Depth Dynamic spatial propagation network for depth completion

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.504627Z

Source-reported events for the cited work

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Observation 135bbd7a-55c6-472e-861a-9b44f8a24afe · outbound

This paper cites RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching.

The Midas Touch for Metric Depth RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.475466Z

Source-reported events for the cited work

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Observation 34659d8e-c3d7-4c86-92bf-c70d8534562d · outbound

This paper cites EfficientViT: Memory Efficient Vision Transformer With Cascaded Group Attention.

The Midas Touch for Metric Depth EfficientViT: Memory Efficient Vision Transformer With Cascaded Group Attention

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.440531Z

Source-reported events for the cited work

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Observation be8e2a95-f3b6-43d2-b43c-cd9f320ab280 · outbound

This paper cites Non-local spatial propagation network for depth completion.

The Midas Touch for Metric Depth Non-local spatial propagation network for depth completion

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.444706Z

Source-reported events for the cited work

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Observation ac17bd03-77d2-4630-83ba-44d6779c14e0 · outbound

This paper cites Depth prompting for sensor-agnostic depth estimation.

The Midas Touch for Metric Depth Depth prompting for sensor-agnostic depth estimation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.448275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b3ba6978-8a5b-4633-b31d-6fd53564859d · outbound

This paper cites Unidepth: Universal monocular metric depth estimation.

The Midas Touch for Metric Depth Unidepth: Universal monocular metric depth estimation

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.422619Z

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Observation 8dea20e6-b97b-4699-80af-e96f260b995a · outbound

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

The Midas Touch for Metric Depth UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-17T09:11:04.541213Z

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Observation 5917344e-93d2-466a-ad47-8f2b6e921cfd · outbound

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

The Midas Touch for Metric Depth Towards robust monocular depth esti- mation: Mixing datasets for zero-shot cross-dataset transfer

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.427219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c0171466-09a3-45d8-a78f-34a41ca2cf39 · outbound

This paper cites Vision Transformers for Dense Prediction.

The Midas Touch for Metric Depth Vision Transformers for Dense Prediction

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.436534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f55a9176-80b1-4acd-a8b4-3bddcd7522e4 · outbound

This paper cites Masked Representation Learning for Domain Generalized Stereo Matching.

The Midas Touch for Metric Depth Masked Representation Learning for Domain Generalized Stereo Matching

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.419888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f2afc4c3-ae0a-4a98-9812-dd9e1b65c313 · outbound

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

The Midas Touch for Metric Depth Hypersim: A photorealistic synthetic dataset for holistic indoor scene understanding

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.465978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8fa0e19a-91ab-4585-8d9a-f0eba0989147 · outbound

This paper cites Make3D: Learning 3D Scene Struc- ture from a Single Still Image.IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(5):824–840.

The Midas Touch for Metric Depth Make3D: Learning 3D Scene Struc- ture from a Single Still Image.IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(5):824–840

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.412404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 15565cfa-6658-4dd1-afa5-2f4418b56763 · outbound

This paper cites A Multi-View Stereo Benchmark With High-Resolution Images and Multi-Camera Videos.

The Midas Touch for Metric Depth A Multi-View Stereo Benchmark With High-Resolution Images and Multi-Camera Videos

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.415930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 082165cb-a96c-4752-9586-c392c391edde · outbound

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

The Midas Touch for Metric Depth Indoor segmentation and support inference from rgbd images

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.432150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7fc4bc87-b028-45ef-866b-784f70591fcc · outbound

This paper cites 5, 9, 12.

The Midas Touch for Metric Depth 5, 9, 12

Reference 46

Resolution: parse uncertain; raw_fallback, observed 2026-05-13T14:42:55.395877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fd889d63-4b80-4b14-829a-7001d9a78934 · outbound

This paper cites Depth Estimation From Camera Image and mmWave Radar Point Cloud.

The Midas Touch for Metric Depth Depth Estimation From Camera Image and mmWave Radar Point Cloud

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.495615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f6665573-a8ab-4768-88ae-87335ca7e827 · outbound

This paper cites SUN RGB-D: A RGB-D Scene Un- derstanding Benchmark Suite.

The Midas Touch for Metric Depth SUN RGB-D: A RGB-D Scene Un- derstanding Benchmark Suite

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.500335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ed50065b-6cd1-413d-8bae-964c122b0d7e · outbound

This paper cites DepthMaster: Taming Diffusion Models for Monocular Depth Estimation.

The Midas Touch for Metric Depth DepthMaster: Taming Diffusion Models for Monocular Depth Estimation

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-05-13T01:37:03.305515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 67a80a46-36f3-4e11-85ee-79dbfe7028aa · outbound

This paper cites LoFTR: Detector-Free Local Fea- ture Matching With Transformers.

The Midas Touch for Metric Depth LoFTR: Detector-Free Local Fea- ture Matching With Transformers

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.390108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6c9cbeaf-1010-4c18-ad50-3337931ef341 · outbound

This paper cites Bilateral propagation network for depth com- pletion.

The Midas Touch for Metric Depth Bilateral propagation network for depth com- pletion

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.392879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c9124c20-3907-4d48-99dc-a7e14bef6824 · outbound

This paper cites Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras.Advances in neu- ral information processing systems (NeurIPS), 34:16558– 16569.

The Midas Touch for Metric Depth Droid-slam: Deep visual slam for monocular, stereo, and rgb-d cameras.Advances in neu- ral information processing systems (NeurIPS), 34:16558– 16569

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.402217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 30e7c7d3-353e-4673-9134-dec828a63d5e · outbound

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

The Midas Touch for Metric Depth DIODE: A Dense Indoor and Outdoor DEpth Dataset

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:37:03.287096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1ba78512-fd07-418f-b4de-94f0fea07504 · outbound

This paper cites Marigold-DC: Zero-Shot Monoc- ular Depth Completion with Guided Diffusion.

The Midas Touch for Metric Depth Marigold-DC: Zero-Shot Monoc- ular Depth Completion with Guided Diffusion

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.377032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9d8c91a1-eae3-4cf2-b6d4-ad0b2cdb213a · outbound

This paper cites G2-MonoDepth: A General Framework of Generalized Depth Inference From Monocular RGB+X Data.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(5):3753–3771.

The Midas Touch for Metric Depth G2-MonoDepth: A General Framework of Generalized Depth Inference From Monocular RGB+X Data.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(5):3753–3771

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.380500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8f74cb5b-995f-4204-b18f-bbc8df615d89 · outbound

This paper cites VGGT: Visual Geometry Grounded Transformer.

The Midas Touch for Metric Depth VGGT: Visual Geometry Grounded Transformer

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.372453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ef26bef6-9415-42e8-b0af-33f82e7c649d · outbound

This paper cites TartanAir: A Dataset to Push the Limits of Visual SLAM.

The Midas Touch for Metric Depth TartanAir: A Dataset to Push the Limits of Visual SLAM

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.539782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ed0e26ca-1b46-4a7d-8598-9acdc4999b2c · outbound

This paper cites Selective-Stereo: Adaptive Frequency In- formation Selection for Stereo Matching.

The Midas Touch for Metric Depth Selective-Stereo: Adaptive Frequency In- formation Selection for Stereo Matching

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.363071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 160e1221-e8ce-49b9-977c-d66ca9c3284d · outbound

This paper cites LRRU: Long-short Range Recurrent Up- dating Networks for Depth Completion.

The Midas Touch for Metric Depth LRRU: Long-short Range Recurrent Up- dating Networks for Depth Completion

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.367241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f9df184f-9655-41da-9e82-469519e64b5d · outbound

This paper cites Behind the scenes: Density fields for single view reconstruction.

The Midas Touch for Metric Depth Behind the scenes: Density fields for single view reconstruction

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.385646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1adad742-9b29-484b-8f33-e16886c6b7c3 · outbound

This paper cites Unsupervised depth completion from visual inertial odometry.IEEE Robotics and Automation Letters, 5 (2):1899–1906.

The Midas Touch for Metric Depth Unsupervised depth completion from visual inertial odometry.IEEE Robotics and Automation Letters, 5 (2):1899–1906

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.406842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 08eeac3a-0d8e-4e75-949e-ae7d077588ac · outbound

This paper cites Tinyvit: Fast pretraining distillation for small vision transformers.

The Midas Touch for Metric Depth Tinyvit: Fast pretraining distillation for small vision transformers

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.453789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 82acc50e-e4be-4797-ab93-8de6cecf82a2 · outbound

This paper cites EfficientSAM: Leveraged Masked Im- age Pretraining for Efficient Segment Anything.

The Midas Touch for Metric Depth EfficientSAM: Leveraged Masked Im- age Pretraining for Efficient Segment Anything

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.488872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c5943aa5-7e61-47bd-b7fe-12248a920c0c · outbound

This paper cites Iterative Geometry Encoding V olume for Stereo Matching.

The Midas Touch for Metric Depth Iterative Geometry Encoding V olume for Stereo Matching

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.566460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dd2f9c68-7d6b-4e59-bd6a-0e2a85fcd76b · outbound

This paper cites IGEV++: Iterative Multi-Range Geome- try Encoding V olumes for Stereo Matching.IEEE Transac- tions on Pattern Analysis and Machine Intelligence, 47(8): 7108–7122.

The Midas Touch for Metric Depth IGEV++: Iterative Multi-Range Geome- try Encoding V olumes for Stereo Matching.IEEE Transac- tions on Pattern Analysis and Machine Intelligence, 47(8): 7108–7122

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.359912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a61943cc-0cc7-48ee-b7b8-51dff1479c85 · outbound

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

The Midas Touch for Metric Depth Depth anything: Unleashing the power of large-scale unlabeled data

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.356127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4cfe7ed4-c61d-4c1f-8cee-f3263e9eeac0 · outbound

This paper cites Depth anything v2.Advances in Neural In- formation Processing Systems (NeurIPS), 37:21875–21911.

The Midas Touch for Metric Depth Depth anything v2.Advances in Neural In- formation Processing Systems (NeurIPS), 37:21875–21911

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.345969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e21b005c-ed20-4a8c-bf79-a9d92a3aa292 · outbound

This paper cites DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data.

The Midas Touch for Metric Depth DiverseDepth: Affine-invariant Depth Prediction Using Diverse Data

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:37:03.282176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3b83e484-2699-4f59-bf26-c1006a7071dd · outbound

This paper cites Learning To Recover 3D Scene Shape From a Single Image.

The Midas Touch for Metric Depth Learning To Recover 3D Scene Shape From a Single Image

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.336665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 127a44b1-0051-4654-8d2d-7db4aa847f47 · outbound

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

The Midas Touch for Metric Depth Metric3d: Towards zero-shot metric 3d predic- tion from a single image

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.350130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 370ee3a3-dbea-4ba9-8255-1b47a0b6bc47 · outbound

This paper cites pixelNeRF: Neural Radiance Fields From One or Few Images.

The Midas Touch for Metric Depth pixelNeRF: Neural Radiance Fields From One or Few Images

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.319957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6c3d38ef-b607-44fb-b256-c7c4228cb4cf · outbound

This paper cites Hierarchical normalization for robust monocular depth estimation.Advances in neural informa- tion processing systems (NeurIPS), 35:14128–14139.

The Midas Touch for Metric Depth Hierarchical normalization for robust monocular depth estimation.Advances in neural informa- tion processing systems (NeurIPS), 35:14128–14139

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.547563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9e5c0b82-0737-423d-8546-c9948e0b5c7a · outbound

This paper cites Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.

The Midas Touch for Metric Depth Faster Segment Anything: Towards Lightweight SAM for Mobile Applications

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:41:43.533652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e7e19137-5e44-427b-b525-4d147443d770 · outbound

This paper cites Domain-invariant stereo matching net- works.

The Midas Touch for Metric Depth Domain-invariant stereo matching net- works

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.571547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ae62fcae-720f-4dfd-8908-17e7a31995b3 · outbound

This paper cites DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation.IEEE Transactions on Image Processing, 34:4258–4272.

The Midas Touch for Metric Depth DCPI-Depth: Explicitly Infusing Dense Correspondence Prior to Unsupervised Monocular Depth Estimation.IEEE Transactions on Image Processing, 34:4258–4272

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.314840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6212926e-b380-49db-8a09-5252d09422a2 · outbound

This paper cites Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation.

The Midas Touch for Metric Depth Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.324731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation abc0e31e-7939-4b02-b1db-00181f6d777d · outbound

This paper cites CompletionFormer: Depth Completion With Convolutions and Vision Transformers.

The Midas Touch for Metric Depth CompletionFormer: Depth Completion With Convolutions and Vision Transformers

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.332969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 4ed4dbad-3df3-4c78-bcf4-8e2c46653821 · outbound

This paper cites Learning representations from foun- dation models for domain generalized stereo matching.

The Midas Touch for Metric Depth Learning representations from foun- dation models for domain generalized stereo matching

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.340522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b52701e1-82ca-440d-89e6-61866b8e1481 · outbound

This paper cites OGNI-DC: Robust depth com- pletion with optimization-guided neural iterations.

The Midas Touch for Metric Depth OGNI-DC: Robust depth com- pletion with optimization-guided neural iterations

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-05-13T14:42:55.307718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Reference resolution

Outbound references

Pith citing papers