Depth as Points: Center Point-based Depth Estimation | Paper Citation Record

Observation 40984d58-2721-4e2b-900f-c4fdfaa71e7a · outbound

This paper cites Analyz- ing factors influencing situation awareness in autonomous vehicles—a survey,.

Depth as Points: Center Point-based Depth Estimation Analyz- ing factors influencing situation awareness in autonomous vehicles—a survey,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:53.065039Z

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Observation 85943452-8fa6-494e-8d80-5d8bf2449b58 · outbound

This paper cites Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions.

Depth as Points: Center Point-based Depth Estimation Why Autonomous Vehicles Are Not Ready Yet: A Multi-Disciplinary Review of Problems, Attempted Solutions, and Future Directions

Reference 2

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Observation ad9571eb-d6f5-4588-abfe-1ac093cebcb2 · outbound

This paper cites A review of environmental perception technology based on multi-sensor information fusion in autonomous driving,.

Depth as Points: Center Point-based Depth Estimation A review of environmental perception technology based on multi-sensor information fusion in autonomous driving,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:53.053241Z

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Observation 9e2e46d5-81f3-4cca-9f06-3d51ceb54a84 · outbound

This paper cites Recent advances in 3d object detection for self-driving vehicles: A survey,.

Depth as Points: Center Point-based Depth Estimation Recent advances in 3d object detection for self-driving vehicles: A survey,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:53.041385Z

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Observation a0a40119-3788-43b2-88b3-c9505146a7c0 · outbound

This paper cites Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving.

Depth as Points: Center Point-based Depth Estimation Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.247644Z

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Observation e3d04130-b4f6-4ebd-8a28-33ab6ffa3178 · outbound

This paper cites M3D-RPN: Monocular 3D Region Proposal Network for Object Detection.

Depth as Points: Center Point-based Depth Estimation M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.252370Z

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Observation af487502-18e3-4652-8d95-92ad75dd9434 · outbound

This paper cites Ground-aware Monocular 3D Object Detection for Autonomous Driving.

Depth as Points: Center Point-based Depth Estimation Ground-aware Monocular 3D Object Detection for Autonomous Driving

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:13:52.632215Z

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Observation 7e26c078-12ac-4324-8674-e1b45b9d2f28 · outbound

This paper cites Mgnet: Monocular geometric scene understanding for autonomous driving,.

Depth as Points: Center Point-based Depth Estimation Mgnet: Monocular geometric scene understanding for autonomous driving,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.260359Z

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Observation 6cdf5251-1e35-4e57-a169-b45630ed8c29 · outbound

This paper cites Vision meets robotics: The kitti dataset,.

Depth as Points: Center Point-based Depth Estimation Vision meets robotics: The kitti dataset,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.264164Z

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Observation 5927e8a1-6030-4846-b181-57fd904eb1b4 · outbound

This paper cites A2D2: Audi Autonomous Driving Dataset.

Depth as Points: Center Point-based Depth Estimation A2D2: Audi Autonomous Driving Dataset

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.267594Z

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Observation df3d16f3-ff3d-48e1-ba1d-b83d514d08f1 · outbound

This paper cites Reverse perspec- tive network for perspective-aware object counting,.

Depth as Points: Center Point-based Depth Estimation Reverse perspec- tive network for perspective-aware object counting,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:53.011333Z

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Observation 9f31a207-1ea2-4fe4-af6d-e46412d88e82 · outbound

This paper cites Uavid: A semantic segmentation dataset for uav imagery,.

Depth as Points: Center Point-based Depth Estimation Uavid: A semantic segmentation dataset for uav imagery,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.997876Z

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Observation 6a862300-3f95-4161-8abc-036a42322be6 · outbound

This paper cites A fully autonomous indoor quadrotor,.

Depth as Points: Center Point-based Depth Estimation A fully autonomous indoor quadrotor,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.984682Z

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Observation 15f294ef-6578-458b-a581-4b8b8521eb0c · outbound

This paper cites Vision-based autonomous mapping and exploration using a quadrotor mav,.

Depth as Points: Center Point-based Depth Estimation Vision-based autonomous mapping and exploration using a quadrotor mav,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.971112Z

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Observation 3b471fc7-6e66-4952-8b6e-81937b715d05 · outbound

This paper cites Estimation, planning, and mapping for autonomous flight using an rgb-d camera in gps-denied environments,.

Depth as Points: Center Point-based Depth Estimation Estimation, planning, and mapping for autonomous flight using an rgb-d camera in gps-denied environments,

Reference 15

Resolution: verified exact; doi, observed 2026-08-16T10:13:52.459073Z

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Observation 09778fbc-3a54-4bd0-88af-735e5a932cd7 · outbound

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

Depth as Points: Center Point-based Depth Estimation nuscenes: A multi- modal dataset for autonomous driving,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.958584Z

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Observation 67d9b328-a331-4f2f-ba4a-579ac224e711 · outbound

This paper cites The apolloscape dataset for autonomous driving,.

Depth as Points: Center Point-based Depth Estimation The apolloscape dataset for autonomous driving,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.946548Z

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Observation f1dad3eb-12da-4568-a0d9-5a5fa7228045 · outbound

This paper cites CARLA: An open urban driving simulator,.

Depth as Points: Center Point-based Depth Estimation CARLA: An open urban driving simulator,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.298423Z

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Observation 2e1f75b1-808a-4c61-9da9-8799a7aa5140 · outbound

This paper cites Pl-slam: Real-time monocular visual slam with points and lines,.

Depth as Points: Center Point-based Depth Estimation Pl-slam: Real-time monocular visual slam with points and lines,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.927272Z

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Observation 7751c6c4-9ea6-46c6-a3b1-66d43fef25b1 · outbound

This paper cites Lift-slam: A deep-learning feature-based monocular visual slam method,.

Depth as Points: Center Point-based Depth Estimation Lift-slam: A deep-learning feature-based monocular visual slam method,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.306337Z

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Observation d964b353-6b5c-472b-95b8-40dc13909c64 · outbound

This paper cites Orbeez-slam: A real-time monocular visual slam with orb features and nerf-realized mapping,.

Depth as Points: Center Point-based Depth Estimation Orbeez-slam: A real-time monocular visual slam with orb features and nerf-realized mapping,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.310121Z

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Observation 5c167a8a-45fc-4bd0-bcd1-76516f83a377 · outbound

This paper cites Multi-sensor fusion self-supervised deep odometry and depth estimation,.

Depth as Points: Center Point-based Depth Estimation Multi-sensor fusion self-supervised deep odometry and depth estimation,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.314389Z

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Observation 538cd140-a500-45b0-a1fe-cf5a6ec4dffe · outbound

This paper cites Multi-sensor depth fusion framework for real-time 3d reconstruction,.

Depth as Points: Center Point-based Depth Estimation Multi-sensor depth fusion framework for real-time 3d reconstruction,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.891107Z

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Observation 387576e1-208a-4af5-af93-61a06b52e696 · outbound

This paper cites OccFusion: Depth Estimation Free Multi-sensor Fusion for 3D Occupancy Prediction.

Depth as Points: Center Point-based Depth Estimation OccFusion: Depth Estimation Free Multi-sensor Fusion for 3D Occupancy Prediction

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:13:52.545022Z

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Observation e34be856-dab7-4f89-bfd5-98890c98ba85 · outbound

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

Depth as Points: Center Point-based Depth Estimation Digging into self-supervised monocular depth estimation,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.326367Z

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Observation 61fd2b59-c5d2-409f-8c37-4d990e8d05e2 · outbound

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

Depth as Points: Center Point-based Depth Estimation Depth anything: Unleashing the power of large-scale unlabeled data,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.329892Z

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Observation d10b24bd-ce5b-4b6e-914d-43b172318f8e · outbound

This paper cites Objects as Points.

Depth as Points: Center Point-based Depth Estimation Objects as Points

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.333583Z

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Observation 9c10010f-85de-4dfc-b474-a6c1ff3fe8ff · outbound

This paper cites Sparse-to-dense: Depth prediction from sparse depth samples and a single image,.

Depth as Points: Center Point-based Depth Estimation Sparse-to-dense: Depth prediction from sparse depth samples and a single image,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.864119Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eb62f813-ffc1-4577-9a62-efabfbc54c2a · outbound

This paper cites Learning guided convolutional network for depth completion,.

Depth as Points: Center Point-based Depth Estimation Learning guided convolutional network for depth completion,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.341259Z

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Observation fac92cba-f424-4517-954c-2a69cc7dd06c · outbound

This paper cites Learning joint 2d-3d representations for depth completion,.

Depth as Points: Center Point-based Depth Estimation Learning joint 2d-3d representations for depth completion,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.845759Z

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Observation 25698536-20fb-47ee-b2c1-7a8d99ad557e · outbound

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

Depth as Points: Center Point-based Depth Estimation Non-local spatial propagation network for depth completion,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.834692Z

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Observation e3f2f0d5-6c00-4c1e-bd7f-dce3e5d2d682 · outbound

This paper cites Dense surface reconstruction from monocular vision and lidar,.

Depth as Points: Center Point-based Depth Estimation Dense surface reconstruction from monocular vision and lidar,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.823037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7e336340-ec33-4351-9d27-930d6f043798 · outbound

This paper cites High-precision depth estimation with the 3d lidar and stereo fusion,.

Depth as Points: Center Point-based Depth Estimation High-precision depth estimation with the 3d lidar and stereo fusion,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.811814Z

Source-reported events for the cited work

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Observation 80091145-6b3d-47ea-9b8c-94ee1e091ca5 · outbound

This paper cites High-precision depth estimation using uncalibrated lidar and stereo fusion,.

Depth as Points: Center Point-based Depth Estimation High-precision depth estimation using uncalibrated lidar and stereo fusion,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.798982Z

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Observation e43fab51-3bea-4fce-99e0-62cf61bc1ac0 · outbound

This paper cites Real-time probabilistic fusion of sparse 3d lidar and dense stereo,.

Depth as Points: Center Point-based Depth Estimation Real-time probabilistic fusion of sparse 3d lidar and dense stereo,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.787744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c77da450-8f94-40a9-a782-d007a7efd35a · outbound

This paper cites Vpfnet: Improving 3d object detection with virtual point based lidar and stereo data fusion,.

Depth as Points: Center Point-based Depth Estimation Vpfnet: Improving 3d object detection with virtual point based lidar and stereo data fusion,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.776019Z

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Observation 943f51af-cb63-496d-9ed1-551fc20a6a83 · outbound

This paper cites 3d lidar and stereo fusion using stereo matching network with con- ditional cost volume normalization,.

Depth as Points: Center Point-based Depth Estimation 3d lidar and stereo fusion using stereo matching network with con- ditional cost volume normalization,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.765077Z

Source-reported events for the cited work

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Observation 2aa217bd-421d-49bd-98cc-0299d5723776 · outbound

This paper cites 3d lidar and stereo fusion using stereo matching network with conditional cost volume normalization. in 2019 ieee,.

Depth as Points: Center Point-based Depth Estimation 3d lidar and stereo fusion using stereo matching network with conditional cost volume normalization. in 2019 ieee,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.753653Z

Source-reported events for the cited work

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Observation 5474f195-bba8-4451-abdd-d564876b822a · outbound

This paper cites Fcos3d: Fully convolutional one- stage monocular 3d object detection,.

Depth as Points: Center Point-based Depth Estimation Fcos3d: Fully convolutional one- stage monocular 3d object detection,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.377206Z

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Observation e9330176-4ffb-4643-b415-e58791fbc5bd · outbound

This paper cites Smoke: Single-stage monocular 3d object detection via keypoint estimation,.

Depth as Points: Center Point-based Depth Estimation Smoke: Single-stage monocular 3d object detection via keypoint estimation,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.736038Z

Source-reported events for the cited work

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Observation f07b7da6-8dd1-439e-9805-d56aa436e0be · outbound

This paper cites Depth Anything V2.

Depth as Points: Center Point-based Depth Estimation Depth Anything V2

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.384575Z

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Observation ac2c338f-d043-4d4f-90a3-b46bd8728ac2 · outbound

This paper cites Unsupervised monocular depth estimation with left-right consistency,.

Depth as Points: Center Point-based Depth Estimation Unsupervised monocular depth estimation with left-right consistency,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.388310Z

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Observation 99246d85-b9bd-421c-9ba4-ab4bb04049ef · outbound

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

Depth as Points: Center Point-based Depth Estimation Make3d: Learning 3d scene structure from a single still image,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.392032Z

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Observation cd3cee40-3e35-4b2b-8d05-ecdf3b0350d6 · outbound

This paper cites A depth estimating method from a single image using foe crf,.

Depth as Points: Center Point-based Depth Estimation A depth estimating method from a single image using foe crf,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.712094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 369bc078-a0eb-41cb-902d-f46748897e46 · outbound

This paper cites Multi-scale contin- uous crfs as sequential deep networks for monocular depth estimation,.

Depth as Points: Center Point-based Depth Estimation Multi-scale contin- uous crfs as sequential deep networks for monocular depth estimation,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.399296Z

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Observation 22e961f4-d800-4806-af83-b83c1c270fbf · outbound

This paper cites Monocular depth esti- mation using multi-scale continuous crfs as sequential deep networks,.

Depth as Points: Center Point-based Depth Estimation Monocular depth esti- mation using multi-scale continuous crfs as sequential deep networks,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.694300Z

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Observation 41bb23e7-0211-43bb-835d-93ab36afb2ed · outbound

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

Depth as Points: Center Point-based Depth Estimation Neural window fully- connected crfs for monocular depth estimation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:52.683169Z

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Observation 8c34e812-94f3-402d-ab07-0d35bfa9baa0 · outbound

This paper cites Virtual KITTI 2.

Depth as Points: Center Point-based Depth Estimation Virtual KITTI 2

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.410101Z

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Observation c8618533-6481-4900-afaa-6af0b303daaf · outbound

This paper cites Is pseudo- lidar needed for monocular 3d object detection?.

Depth as Points: Center Point-based Depth Estimation Is pseudo- lidar needed for monocular 3d object detection?

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.414139Z

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Observation 45748916-e488-4739-9426-418f959a3224 · outbound

This paper cites BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers.

Depth as Points: Center Point-based Depth Estimation BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.417710Z

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Unavailable: canonical work link unavailable.

Observation 9dfd7107-89d1-49fa-a264-6c13b98c0283 · outbound

This paper cites Deformable Convolutional Networks.

Depth as Points: Center Point-based Depth Estimation Deformable Convolutional Networks

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-16T10:13:52.421636Z

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Observation 85ca679e-a68a-4350-888a-785e297af8f7 · outbound

This paper cites An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection.

Depth as Points: Center Point-based Depth Estimation An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:13:52.476131Z

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Observation 8bf9d330-69b7-4462-bcd1-f3d7b67a89f1 · outbound

This paper cites Available: https://www.mdpi.com/2673-2688/5/3/61.

Depth as Points: Center Point-based Depth Estimation Available: https://www.mdpi.com/2673-2688/5/3/61

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:13:53.029880Z

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