PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency | Paper Citation Record

Observation 67779b8a-be8c-4096-a55d-a414c89a34b4 · outbound

This paper cites Revisiting depth completion from a stereo matching perspective for cross-domain generalization.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Revisiting depth completion from a stereo matching perspective for cross-domain generalization

Reference 1

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Observation 8497b84c-85cd-46aa-8420-d9aa61e8c9fc · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Depth Pro: Sharp Monocular Metric Depth in Less Than a Second

Reference 2

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Observation a0591ba2-b5db-4e5a-8fe3-2e9ab44bd4ef · outbound

This paper cites A naturalistic open source movie for op- tical flow evaluation.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency A naturalistic open source movie for op- tical flow evaluation

Reference 3

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Observation b32a675b-b2be-49da-96c1-d127de3f9d22 · outbound

This paper cites Orb-slam3: An accu- rate open-source library for visual, visual–inertial, and mul- timap slam.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Orb-slam3: An accu- rate open-source library for visual, visual–inertial, and mul- timap slam

Reference 4

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Observation 5e3ab9d6-d25d-4c31-bf6d-45494468aabb · outbound

This paper cites Matterport3D: Learning from RGB-D Data in Indoor Environments.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Matterport3D: Learning from RGB-D Data in Indoor Environments

Reference 5

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Observation 788d581c-eb18-4470-a41f-71045ba04637 · outbound

This paper cites Depth com- pletion using geometry-aware embedding.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Depth com- pletion using geometry-aware embedding

Reference 6

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Observation 3fe61b3c-f0a3-42ee-99ec-9ba5a80d47f0 · outbound

This paper cites Learning depth with convolutional spatial propagation network.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Learning depth with convolutional spatial propagation network

Reference 7

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Observation 21292439-e873-4065-8709-a67605bb63cf · outbound

This paper cites Spar- sity agnostic depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Spar- sity agnostic depth completion

Reference 8

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Observation 899ba14a-f081-4ce6-ade7-916ed5e139ab · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Deep ordinal regression net- work for monocular depth estimation

Reference 9

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Observation fb8509d6-7692-4a38-8add-0dd2217090d0 · outbound

This paper cites Virtual worlds as proxy for multi-object tracking anal- ysis.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Virtual worlds as proxy for multi-object tracking anal- ysis

Reference 10

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Observation f725ae1d-b349-431a-8afe-c642a57d6c9d · outbound

This paper cites Are we ready for autonomous driving? the kitti vision bench- mark suite.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Are we ready for autonomous driving? the kitti vision bench- mark suite

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:27.951867Z

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Observation b60ef846-70ee-4916-8ac8-e7f9a7ee3d19 · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency 3d packing for self-supervised monocular depth estimation

Reference 12

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Observation d298a8ef-e529-45bc-b775-11b57b36e708 · outbound

This paper cites Sparse auxiliary networks for unified monocular depth prediction and completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Sparse auxiliary networks for unified monocular depth prediction and completion

Reference 13

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Observation 2687ef2f-341b-4b80-8b49-1803b0d5ea40 · outbound

This paper cites Distill any depth: Distillation cre- ates a stronger monocular depth estimator.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Distill any depth: Distillation cre- ates a stronger monocular depth estimator

Reference 14

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Observation 6458248d-6288-4599-9f92-55fd2f2c47d8 · outbound

This paper cites Penet: Towards precise and efficient image guided depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Penet: Towards precise and efficient image guided depth completion

Reference 15

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Observation b37b4b01-8455-4072-9e32-4a11cf720004 · outbound

This paper cites Depth com- pletion with twin surface extrapolation at occlusion bound- aries.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Depth com- pletion with twin surface extrapolation at occlusion bound- aries

Reference 16

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Observation b6f43f32-a213-48c3-886a-5ad248f9d2de · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Repurpos- ing diffusion-based image generators for monocular depth estimation

Reference 17

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Observation d6553b77-e6cf-422c-b1d6-360f1ebb15ff · outbound

This paper cites Con- match: Semi-supervised learning with confidence-guided consistency regularization.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Con- match: Semi-supervised learning with confidence-guided consistency regularization

Reference 18

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Observation dd4a14ad-b8b4-43d3-9bf7-989bec89f5af · outbound

This paper cites Segment any- thing.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Segment any- thing

Reference 19

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Observation 5b304de6-99b9-4863-b417-ef465a64ca1a · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Evaluation of cnn-based single-image depth estimation methods

Reference 20

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Observation e2dc0780-224c-491a-9804-eee53a779dd7 · outbound

This paper cites Comatch: Semi-supervised learning with contrastive graph regulariza- tion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Comatch: Semi-supervised learning with contrastive graph regulariza- tion

Reference 21

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Observation 168467dd-8acc-4138-a7a0-df8c879f7299 · outbound

This paper cites SemiReward: A General Reward Model for Semi-supervised Learning.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency SemiReward: A General Reward Model for Semi-supervised Learning

Reference 22

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Observation 3f92dfd2-d91c-491a-8f93-9f5814bbe69b · outbound

This paper cites Dis- tilling monocular foundation model for fine-grained depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Dis- tilling monocular foundation model for fine-grained depth completion

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:45.042836Z

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Observation a523a881-fac0-419e-b21e-99a824e85350 · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Swin transformer: Hierarchical vision transformer using shifted windows

Reference 24

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Observation c6b8def7-7613-4125-b9c6-fc80d47cf44b · outbound

This paper cites Sparsedc: Depth completion from sparse and non-uniform inputs.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Sparsedc: Depth completion from sparse and non-uniform inputs

Reference 25

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Observation 61b2a66b-7041-440a-8909-3e6d62346bfd · outbound

This paper cites Self-supervised sparse-to-dense: Self-supervised depth completion from lidar and monocular camera.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Self-supervised sparse-to-dense: Self-supervised depth completion from lidar and monocular camera

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:44.754990Z

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Observation 3c5295fe-478c-441a-95d7-180b88bf80ec · outbound

This paper cites OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency OccDepth: A Depth-Aware Method for 3D Semantic Scene Completion

Reference 27

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Observation ad80ac72-2b2e-4398-8f9f-9956169eff8f · outbound

This paper cites Semattnet: Toward attention- based semantic aware guided depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Semattnet: Toward attention- based semantic aware guided depth completion

Reference 28

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Observation 46b3c229-d667-4338-bac7-de49968d3034 · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Non-local spatial propagation network for depth completion

Reference 29

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Observation 6c61084b-9c5b-4a3c-a589-fbe5d528fc53 · outbound

This paper cites A simple yet universal framework for depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency A simple yet universal framework for depth completion

Reference 30

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Observation c13ab8ce-e85c-4ae7-9a86-33fa23a46685 · outbound

This paper cites Learning affinity with hyperbolic representation for spatial propagation.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Learning affinity with hyperbolic representation for spatial propagation

Reference 31

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Observation 98091c98-2238-43b0-8ecb-b15f467f9509 · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Depth prompting for sensor-agnostic depth estimation

Reference 32

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Observation 5c5c4a88-70ad-4a9f-832b-8dc045d975ad · outbound

This paper cites Unidepth: Universal monocular metric depth estimation.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Unidepth: Universal monocular metric depth estimation

Reference 33

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Observation 07848598-2a2b-492f-acc3-88a8841a7fa1 · outbound

This paper cites Deepli- dar: Deep surface normal guided depth prediction for out- door scene from sparse lidar data and single color image.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Deepli- dar: Deep surface normal guided depth prediction for out- door scene from sparse lidar data and single color image

Reference 34

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Observation 99672871-606b-48c1-837f-371d6433fae8 · outbound

This paper cites Few- shot depth completion using denoising diffusion probabilis- tic model.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Few- shot depth completion using denoising diffusion probabilis- tic model

Reference 35

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Observation 3a959ad3-544d-4ec6-b641-d97b0cff1972 · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer

Reference 36

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Observation 15b401b0-3b69-4866-ae58-fa19ddbf5f16 · outbound

This paper cites Vi- sion transformers for dense prediction.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Vi- sion transformers for dense prediction

Reference 37

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Observation 94cac921-7b48-4da7-9553-98adf8c484df · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency SAM 2: Segment Anything in Images and Videos

Reference 38

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This paper cites Guide- former: Transformers for image guided depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Guide- former: Transformers for image guided depth completion

Reference 39

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Observation a771d100-8c00-494c-bba9-a7193aac8875 · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency A multi-view stereo benchmark with high- resolution images and multi-camera videos

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:43.076684Z

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Observation f7e0b79c-4862-4e0b-9daa-b0aada0be3e4 · outbound

This paper cites Towards comprehensive monocular depth estimation: Mul- tiple heads are better than one.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Towards comprehensive monocular depth estimation: Mul- tiple heads are better than one

Reference 41

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Observation e1dfad8d-9ab6-40bf-8dfc-ccf07113e70f · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Indoor segmentation and support inference from rgbd images

Reference 42

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Observation 8ecad808-c1c4-47bb-ac61-dde631255e55 · outbound

This paper cites Fixmatch: Simpli- fying semi-supervised learning with consistency and confi- dence.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Fixmatch: Simpli- fying semi-supervised learning with consistency and confi- dence

Reference 43

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Observation 8fcb4d81-1b44-41d0-b8cc-e30d98b4cedf · outbound

This paper cites Self-supervised depth completion from direct visual-lidar odometry in autonomous driving.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Self-supervised depth completion from direct visual-lidar odometry in autonomous driving

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:42.353283Z

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Observation bec4d9ce-2478-4f26-a61a-18920f20ebb0 · outbound

This paper cites Bilateral propagation network for depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Bilateral propagation network for depth completion

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:42.231995Z

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Observation 7b117650-4b64-45e7-ae38-d84a9059da53 · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency DIODE: A Dense Indoor and Outdoor DEpth Dataset

Reference 46

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Observation 02f26914-6df3-4aa0-bf21-0463f68afdd5 · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Marigold-DC: Zero-Shot Monocular Depth Completion with Guided Diffusion

Reference 47

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Observation 9128c884-1777-4e4a-9a4f-9e49e6f3b5b8 · outbound

This paper cites Depth map recovery based on a unified depth boundary distortion model.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Depth map recovery based on a unified depth boundary distortion model

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:42.032728Z

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Observation 066eefa3-cf22-461d-830d-311e29498a76 · outbound

This paper cites Rgb-guided depth map recovery by two-stage coarse-to-fine dense crf models.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Rgb-guided depth map recovery by two-stage coarse-to-fine dense crf models

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:41.844924Z

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Observation 58399635-4be4-4400-a391-5fff8dcc5d14 · outbound

This paper cites G2- monodepth: A general framework of generalized depth in- ference from monocular rgb+ x data.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency G2- monodepth: A general framework of generalized depth in- ference from monocular rgb+ x data

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:41.659701Z

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Observation 351b49db-1330-4092-8f0c-f33db7ddfaa3 · outbound

This paper cites Scale propagation network for generalizable depth comple- tion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Scale propagation network for generalizable depth comple- tion

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:41.505403Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3a6b147a-0d71-4f86-8083-a3c78bd4a266 · outbound

This paper cites Dust3r: Geometric 3d vi- sion made easy.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Dust3r: Geometric 3d vi- sion made easy

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:41.343136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f67cd4d3-b0ea-48a6-a675-a6a3bc12ee7a · outbound

This paper cites FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:32.690986Z

Source-reported events for the cited work

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Observation 95c7ccb9-3690-45ac-b849-091d01649d62 · outbound

This paper cites Lrru: Long-short range recurrent updating networks for depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Lrru: Long-short range recurrent updating networks for depth completion

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:41.083538Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation baf8e932-d1f7-4605-ae2f-1ccb400e7faa · outbound

This paper cites Improving depth completion via depth feature upsampling.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Improving depth completion via depth feature upsampling

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:40.788457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 00eec549-2a52-4702-8d10-38f226506275 · outbound

This paper cites Monocular visual-inertial depth estimation.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Monocular visual-inertial depth estimation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:40.434361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fc9cde21-6167-4b18-abfe-bc168f06e202 · outbound

This paper cites Unsupervised depth comple- tion with calibrated backprojection layers.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Unsupervised depth comple- tion with calibrated backprojection layers

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:40.122141Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation abc50c2e-4957-4be0-9620-c0c165fa8bd8 · outbound

This paper cites Unsupervised depth completion from visual iner- tial odometry.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Unsupervised depth completion from visual iner- tial odometry

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:39.740570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1b07db50-4502-425a-a01f-a71b040ec3e1 · outbound

This paper cites Con- vnext v2: Co-designing and scaling convnets with masked autoencoders.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Con- vnext v2: Co-designing and scaling convnets with masked autoencoders

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:39.392613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8671e8d6-0237-41a7-a3c4-f6a37d860749 · outbound

This paper cites Convolution with even-sized kernels and symmetric padding.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Convolution with even-sized kernels and symmetric padding

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:39.254592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 184ddc45-9ca7-43e4-a920-32b8168ea385 · outbound

This paper cites Augundo: Scaling up augmentations for monocular depth completion and estima- tion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Augundo: Scaling up augmentations for monocular depth completion and estima- tion

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:39.181516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 116423b4-beb6-42fd-8709-6ca3f793c840 · outbound

This paper cites Structure-guided ranking loss for single im- age depth prediction.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Structure-guided ranking loss for single im- age depth prediction

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:39.004925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f628716c-b753-4e70-872f-f778e3594aba · outbound

This paper cites Unsupervised data augmentation for consistency training.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Unsupervised data augmentation for consistency training

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:38.774554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 67e4f46c-8a3b-4259-aff6-86168c7df34d · outbound

This paper cites Self-training with noisy student improves imagenet clas- sification.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Self-training with noisy student improves imagenet clas- sification

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:33.637920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87d00e9d-ab50-4110-a60c-0a8b79ceaab3 · outbound

This paper cites Towards domain-agnostic depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Towards domain-agnostic depth completion

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:38.627804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d1f40602-1b65-4fb5-86fd-2ddb8375eef8 · outbound

This paper cites Depth completion from sparse li- dar data with depth-normal constraints.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Depth completion from sparse li- dar data with depth-normal constraints

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:38.507617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 371c1f8c-3430-4f52-82e0-8184816963db · outbound

This paper cites Desnet: Decomposed scale-consistent net- work for unsupervised depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Desnet: Decomposed scale-consistent net- work for unsupervised depth completion

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:38.387854Z

Source-reported events for the cited work

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Observation a93c6d19-b7f5-4858-929f-d9a46247b9e8 · outbound

This paper cites Tri- perspective view decomposition for geometry-aware depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Tri- perspective view decomposition for geometry-aware depth completion

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:38.283407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0b4bf9d9-1fbd-424e-8c82-722a5f449fb5 · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Depth anything: Unleashing the power of large-scale unlabeled data

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:38.184658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8cc15afa-6884-4ff0-a49e-e36f265e4953 · outbound

This paper cites Depth any- thing v2.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Depth any- thing v2

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:38.101985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5ebfd69f-054c-4877-82cb-881dffd0b80c · outbound

This paper cites Blendedmvs: A large- scale dataset for generalized multi-view stereo networks.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Blendedmvs: A large- scale dataset for generalized multi-view stereo networks

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:38.002859Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4e201772-724e-4136-a539-edeac2e2673d · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Virtual normal: En- forcing geometric constraints for accurate and robust depth prediction

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:37.810527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a93cc79c-9d5d-46e8-b414-699ef0fc5c3e · outbound

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

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Metric3d: Towards zero-shot metric 3d prediction from a single image

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:34.436830Z

Source-reported events for the cited work

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Observation d59bec07-f5be-4348-97c5-334cd2a10405 · outbound

This paper cites Neural window fully-connected crfs for monocu- lar depth estimation.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Neural window fully-connected crfs for monocu- lar depth estimation

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:34.537918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfe0d7a1-2601-4b83-9434-525f051adb2f · outbound

This paper cites Flexmatch: Boosting semi-supervised learning with curricu- lum pseudo labeling.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Flexmatch: Boosting semi-supervised learning with curricu- lum pseudo labeling

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:37.619409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7e709a12-d095-487c-8702-2ad5f999752f · outbound

This paper cites Multitask gans for se- mantic segmentation and depth completion with cycle con- sistency.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Multitask gans for se- mantic segmentation and depth completion with cycle con- sistency

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:37.423350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3c0e38bc-40de-4a8c-8ebe-4607fb029506 · outbound

This paper cites Deep depth comple- tion of a single rgb-d image.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Deep depth comple- tion of a single rgb-d image

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:37.242682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d690de67-a152-45b0-a72a-28357ac4c281 · outbound

This paper cites Completionformer: Depth completion with convolutions and vision transform- ers.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Completionformer: Depth completion with convolutions and vision transform- ers

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:37.087564Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 42b9f07d-fa70-4777-92b5-21a9365b1d74 · outbound

This paper cites Bev@ dc: Bird’s-eye view assisted training for depth completion.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Bev@ dc: Bird’s-eye view assisted training for depth completion

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:36.905005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c600243d-dc20-4df0-a7c0-98850cad6987 · outbound

This paper cites Semi-supervised learning by disagreement.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Semi-supervised learning by disagreement

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:36.663280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 981c1388-e1de-407a-9eb3-9b6a1b686ca3 · outbound

This paper cites Ogni-dc: Robust depth comple- tion with optimization-guided neural iterations.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Ogni-dc: Robust depth comple- tion with optimization-guided neural iterations

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:35.143932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d67e4cb-e018-4794-997d-7a293415c63d · outbound

This paper cites OMNI-DC: Highly Robust Depth Completion with Multiresolution Depth Integration.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency OMNI-DC: Highly Robust Depth Completion with Multiresolution Depth Integration

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T18:49:35.231794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ed92dd0-0dc6-4f79-99e0-119739eb9c72 · outbound

This paper cites Ours-T” even outperforms “SPNet-L.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency Ours-T” even outperforms “SPNet-L

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:36.468407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 99ec2c9d-a5e5-4307-bd1a-554d07a41af2 · outbound

This paper cites We fur- ther evaluate PacGDC on the DDAD [12] dataset, compar- ing to more generalizable and supervised baselines, follow- ing the standard protocol of VPP4DC [1].

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency We fur- ther evaluate PacGDC on the DDAD [12] dataset, compar- ing to more generalizable and supervised baselines, follow- ing the standard protocol of VPP4DC [1]

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:36.278789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e85418d2-fb61-4455-b0ad-2f674c8244b7 · outbound

This paper cites We evaluate our approach with four different depth foundation mod- els: DepthAnything (DA) [69], DepthPro [2], DepthAny- thingV2 (DA V2) [70], and DistillAnyDepth (DistillAD) [14].

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency We evaluate our approach with four different depth foundation mod- els: DepthAnything (DA) [69], DepthPro [2], DepthAny- thingV2 (DA V2) [70], and DistillAnyDepth (DistillAD) [14]

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:36.056591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 782ff79d-5f27-4614-b77f-834d856a0c5e · outbound

This paper cites We further provide visual examples of zero-shot scenarios in Fig.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency We further provide visual examples of zero-shot scenarios in Fig

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:35.903808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2019d9cf-5e1f-42d7-bc79-ffdaeb809258 · outbound

This paper cites 1, 2, 3, 6, 8.

PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency 1, 2, 3, 6, 8

Reference 3361

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:49:46.466305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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