Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T17:44:02.865312Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2502.05859.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T17:44:02.865312Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
63 of 63 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 5940d881-0f30-4913-9d6a-4c3072d6b74f · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Pano3d: A holistic benchmark and a solid baseline for 360deg depth estimation
Reference 1
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Observation 87474b7b-7f6e-4547-909f-3a0912452b2f · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion High Quality Monocular Depth Estimation via Transfer Learning
Reference 2
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Observation ed70e1c3-feaf-484c-9d00-a702bb157b3d · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Joint 2D-3D-Semantic Data for Indoor Scene Understanding
Reference 3
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SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Adabins: Depth estimation using adaptive bins
Reference 4
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Observation c3e08a22-2d5d-4f0c-9153-a45abc9eb145 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Unsupervised scale-consistent depth learning from video.In- ternational Journal of Computer Vision, 129(9):2548–2564,
Reference 5
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Observation 14810967-dc8c-4c8f-95a6-4532d3f60b58 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Matterport3D: Learning from RGB-D Data in Indoor Environments
Reference 6
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Observation abbb23eb-9169-4718-8bbb-3c7eb358f705 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Distortion-aware monocular depth estimation for omnidirectional images
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SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Cube padding for weakly-supervised saliency prediction in 360 videos
Reference 8
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SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Omnidirectional depth extension networks
Reference 9
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Observation e72fc224-7ce7-4b75-9456-774b6571e6a2 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Reference 10
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Observation 4db42249-313c-45bf-adb4-026f46a903b8 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion MeshLab: an Open-Source Mesh Processing Tool
Reference 11
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Observation 9b4bdaff-f870-4e67-bbae-f3b0249054fa · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Spherical CNNs
Reference 12
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Observation 2b0ddce4-4823-41f4-8e25-ea44ade4b216 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Eliminating the blind spot: Adapting 3d object detection and monocular depth estimation to 360 panoramic imagery
Reference 13
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Observation 80e0a622-025b-4915-b17f-cd43051f5fff · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion An image is worth 16x16 words: Transformers for image recognition at scale
Reference 14
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Observation d74a1c32-21db-4f33-8e13-4118cb72680b · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Pano popups: In- door 3d reconstruction with a plane-aware network
Reference 15
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Observation 9def1480-94c0-4f9e-b329-f99320cf17e3 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Mapped Convolutions
Reference 16
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Observation e319b931-a945-4174-9dbe-02c7df3ab2f0 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Tangent images for mitigating spherical distortion
Reference 17
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Observation cb3a7baf-c1a1-4409-b193-a3800f713a0d · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Predicting depth, surface nor- mals and semantic labels with a common multi-scale con- volutional architecture
Reference 18
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Observation 53950acc-5ce5-4d39-8431-17a03de80d53 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Depth map prediction from a single image using a multi-scale deep net- work
Reference 19
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SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Meshnet: Mesh neural network for 3d shape rep- resentation
Reference 20
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Observation 261ba8b0-bfb3-436d-b98c-ec63130c6793 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Corners for layout: End-to-end layout recovery from 360 images
Reference 21
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Observation f9bd146f-41a6-467d-85a9-fc20aa7d2b5c · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Digging into self-supervised monocular depth estimation
Reference 22
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Observation b88bfb7b-e640-4840-8bbd-c73d8d526380 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Meshcnn: a network with an edge
Reference 23
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Observation 8ebca19d-21d5-467c-83a6-38cffc809d07 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Deep residual learning for image recognition
Reference 24
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Observation 650917b1-0efe-4312-b1d9-e0232b6beab2 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Auto- matic photo pop-up
Reference 25
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Observation b33691fb-1cdb-4d36-a80b-3b8fc5b9fb35 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Jittor: a novel deep learning framework with meta-operators and unified graph execution
Reference 26
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Observation 3b19ea28-4095-40ff-bec7-857f6106d219 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Subdivision-based mesh convolution networks
Reference 27
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Observation 8735c9fa-ef50-4291-b12f-ad5376d3468b · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Spherical CNNs on Unstructured Grids
Reference 28
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Observation c2d1e3b4-bbd8-43ad-87bf-26cd3f73d0b2 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Unifuse: Unidirectional fusion for 360 panorama depth estimation
Reference 29
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Observation 711cbe80-f43d-4c19-a1cc-83d74972c353 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Geometric structure based and regularized depth estimation from 360 indoor imagery
Reference 30
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Observation d09ed414-3ded-4b98-822a-c65ebdf10254 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Himode: A hybrid monocular omnidirectional depth estimation model
Reference 31
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Observation 1d9d7721-9061-4f09-85ef-ad7ef233d3fd · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Deeper depth prediction with fully convolutional residual networks
Reference 32
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Observation c3595f34-de1a-4ec2-abdc-fbb273f30718 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Spherephd: Applying cnns on 360° images with non-euclidean spherical polyhedron represen- tation
Reference 33
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Observation 381d494d-ae4d-4695-b0a7-00dfca89f2ee · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Omnifusion: 360 monocular depth estimation via geometry-aware fusion
Reference 34
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Observation 0170239c-f98e-4ba1-8872-81a997472cb8 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion P3depth: Monocular depth estimation with a piecewise planarity prior
Reference 35
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Observation 3c4362ee-87fe-43ea-8bd3-b98e85d27afc · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion High-Resolution Depth Estimation for 360-degree Panoramas through Perspective and Panoramic Depth Images Registration
Reference 36
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Observation a23e11f4-e3ba-43e9-9441-0df59749cb7b · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Slicenet: deep dense depth esti- mation from a single indoor panorama using a slice-based representation
Reference 37
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Observation 080a882b-38f8-47c6-8b43-fd1c6f8695ce · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
Reference 38
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Observation 2c5b80bf-b90c-40b9-8969-192c3ab135b9 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion 360monodepth: High-resolution 360deg monocular depth estimation
Reference 39
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Observation 76f03ef8-3094-4926-8e02-2b0dd1885fbf · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion U- net: Convolutional networks for biomedical image segmen- tation
Reference 40
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Observation b6eef0de-1a59-4a33-9620-7e14abf74754 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Make3d: Learning 3d scene structure from a single still image
Reference 41
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Observation 1f0b7f61-b5b1-411e-9406-35249bbb3573 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Panoformer: Panorama transformer for indoor 360 depth estimation
Reference 42
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Observation 992951ad-d4c4-4218-b10a-b34684d02511 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Neural contourlet network for monocular 360 depth estimation
Reference 43
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SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Standardization status of 360 degree video coding and delivery
Reference 44
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Observation 961f9501-7840-42cd-8915-990dfb51b878 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Kernel transformer net- works for compact spherical convolution
Reference 45
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SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Hohonet: 360 indoor holistic understanding with latent horizontal fea- tures
Reference 46
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Observation 238b096e-a53d-4409-bf61-6abe3426fd66 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Distortion-aware convolutional filters for dense prediction in panoramic images
Reference 47
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Observation a20e8b50-dcac-4ffa-9e32-c25a5e7c81bc · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Bifuse: Monocular 360 depth estimation via bi-projection fusion
Reference 48
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Observation a4ae2eeb-d6da-475e-b3d0-0be7ab18a926 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion 360sd-net: 360 stereo depth estimation with learnable cost volume
Reference 49
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Observation a8ae84ee-78f7-43a5-b061-abbca2600b80 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion The temporal opportunist: Self-supervised multi-frame monocular depth
Reference 50
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Observation 4e8fa302-b4e2-45e7-ad10-52d808e9ac53 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Spheredepth: Panorama depth estima- tion from spherical domain
Reference 51
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Observation 4c61b944-5f0b-4214-ab93-82cceee362c4 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Virtual normal: En- forcing geometric constraints for accurate and robust depth prediction
Reference 52
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Observation 6e5c599b-d719-4364-9ef7-441e5fd9a2c3 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Flat2sphere: Learning spheri- cal convolution for fast features from 360 imagery
Reference 53
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Observation 8b2e025f-7589-495c-a689-96fdac4dcfca · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion NeW CRFs: Neural Window Fully-connected CRFs for Monocular Depth Estimation
Reference 54
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SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Joint 3d layout and depth prediction from a single indoor panorama image
Reference 55
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SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion To- wards better generalization: Joint depth-pose learning with- out posenet
Reference 56
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Observation 23b1715e-0eab-4de1-9d50-de3fb8e78522 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Structured3d: A large photo-realistic dataset for structured 3d modeling
Reference 57
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Observation a27e9aa1-de7d-4288-a320-8f774a93fdf8 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Unsupervised learning of depth and ego-motion from video
Reference 58
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Observation 644f47c2-6754-49dd-8d90-a3c25e416b1b · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Omnidepth: Dense depth estimation for indoors spherical panoramas
Reference 59
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Observation 32baaf1c-3082-42ba-9c8b-9fcec1a66b0a · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Unresolved cited work
Reference 60
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Observation 9d1b3499-8767-4d74-be67-e694da288b40 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Fol- lowing BiFuse [48], we use five evaluation metrics, includ- ing MAE, MRE, RMSE, RMSE(log), and δn
Reference 61
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Observation 04ca2d2b-15cf-481c-b82d-abd175056e71 · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion On 360D [59], we compare our method with SphereDepth [51] and UniFuse [29]
Reference 62
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Observation 85e9cf98-a085-41d5-b034-d4c46031d04e · outbound
SphereFusion: Efficient Panorama Depth Estimation via Gated Fusion Figure 12 and Fig- ure 13 show depth maps generated by different methods on Matterport3D and corresponding point clouds
Reference 63
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No inbound Pith citation observations are available.