CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images | Paper Citation Record

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This paper cites Mip-nerf: A multiscale representation for anti-aliasing neu- ral radiance fields.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Mip-nerf: A multiscale representation for anti-aliasing neu- ral radiance fields

Reference 1

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Observation ea460774-7b35-4bfe-8afd-7e3b9cf37b1e · outbound

This paper cites A neural approach to blind motion deblur- ring.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images A neural approach to blind motion deblur- ring

Reference 2

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Observation dca8ea5b-7006-4cae-922f-9be57449374e · outbound

This paper cites Tensorf: Tensorial radiance fields.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Tensorf: Tensorial radiance fields

Reference 3

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Observation 8e83c405-9272-4fe4-a895-28dd3ddc40d8 · outbound

This paper cites Deblur-gs: 3d gaussian splat- ting from camera motion blurred images.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Deblur-gs: 3d gaussian splat- ting from camera motion blurred images

Reference 4

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This paper cites Blender - a 3D modelling and rendering package.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Blender - a 3D modelling and rendering package

Reference 5

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Observation 6e4deb1f-d12e-4837-8901-13993b88adb7 · outbound

This paper cites Plenoxels: Radiance fields without neural networks.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Plenoxels: Radiance fields without neural networks

Reference 6

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CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Unresolved cited work

Reference 7

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Observation 823b0e5a-a413-4199-badf-f5d28a8f8a26 · outbound

This paper cites Neuman: Neural human radiance field from a single video.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Neuman: Neural human radiance field from a single video

Reference 8

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Observation c4b095be-5faf-4285-999e-fe59d9a10625 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images 3d gaussian splatting for real-time radiance field rendering

Reference 9

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Observation d85a8f4c-31e1-496a-918a-e673b4397a31 · outbound

This paper cites Deblurring 3D Gaussian Splatting.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Deblurring 3D Gaussian Splatting

Reference 10

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Observation 934b6fcd-e5fc-4317-809f-635369ac8d62 · outbound

This paper cites Dp-nerf: Deblurred neural radiance field with physical scene priors.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Dp-nerf: Deblurred neural radiance field with physical scene priors

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:57:40.341739Z

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Observation 85a8961a-7b62-499c-a948-67ba047b7995 · outbound

This paper cites CRiM-GS: Continuous Rigid Motion-Aware Gaussian Splatting from Motion-Blurred Images.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images CRiM-GS: Continuous Rigid Motion-Aware Gaussian Splatting from Motion-Blurred Images

Reference 12

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Observation e3daef12-790c-4784-8ff6-4c671c91062b · outbound

This paper cites SMURF: Continuous Dynamics for Motion-Deblurring Radiance Fields.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images SMURF: Continuous Dynamics for Motion-Deblurring Radiance Fields

Reference 13

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Observation 4b484d8b-b9fd-49dc-a5a2-740a33df7bdb · outbound

This paper cites Neural 3d video synthesis from multi-view video.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Neural 3d video synthesis from multi-view video

Reference 14

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Observation 5ea21534-dec9-471e-bdba-503b0bce4190 · outbound

This paper cites Neural scene flow fields for space-time view synthesis of dy- namic scenes.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Neural scene flow fields for space-time view synthesis of dy- namic scenes

Reference 15

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Observation 039fa02c-a1d8-450e-a32a-e33b84f566df · outbound

This paper cites Neuralangelo: High-fidelity neural surface reconstruction.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Neuralangelo: High-fidelity neural surface reconstruction

Reference 16

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Observation 4d0b02c0-dced-4fcd-aa1a-abe8098d23d5 · outbound

This paper cites Modern robotics.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Modern robotics

Reference 17

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Observation 2a03ebbd-f638-4aa6-a8dc-acf28fdf56f1 · outbound

This paper cites Deblur-nerf: Neural radiance fields from blurry images.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Deblur-nerf: Neural radiance fields from blurry images

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:57:40.273404Z

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Observation f79309b3-5571-401c-8ba5-107d3e6aa55e · outbound

This paper cites Local light field fusion: Practical view syn- thesis with prescriptive sampling guidelines.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Local light field fusion: Practical view syn- thesis with prescriptive sampling guidelines

Reference 19

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Observation 9c1e1c32-de0e-4952-8853-4838f01613e8 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view syn- thesis.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Nerf: Representing scenes as neural radiance fields for view syn- thesis

Reference 20

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Observation 7e1ac94b-7ee9-448f-8519-7e22c21fbf6c · outbound

This paper cites Instant neural graphics primitives with a mul- tiresolution hash encoding.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Instant neural graphics primitives with a mul- tiresolution hash encoding

Reference 21

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Observation 8c411642-f1b7-43ef-b4b0-3733e82808c4 · outbound

This paper cites Reg- nerf: Regularizing neural radiance fields for view synthesis from sparse inputs.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Reg- nerf: Regularizing neural radiance fields for view synthesis from sparse inputs

Reference 22

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Observation a7698b08-88ec-4389-be39-eff3dc9d5642 · outbound

This paper cites Nerfies: Deformable neural radiance fields.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Nerfies: Deformable neural radiance fields

Reference 23

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Observation d404a6ff-746b-4cf7-a9fb-d85a9eb3e3da · outbound

This paper cites HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields

Reference 24

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Observation f1ce8431-1e14-4e8b-a1cc-56a7b40d8fc1 · outbound

This paper cites Pdrf: progressively de- blurring radiance field for fast scene reconstruction from blurry images.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Pdrf: progressively de- blurring radiance field for fast scene reconstruction from blurry images

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:57:40.191316Z

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Observation 9e1bd1b8-1875-4ece-8844-795bcb5438a2 · outbound

This paper cites BAGS: Blur Agnostic Gaussian Splatting through Multi-Scale Kernel Modeling.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images BAGS: Blur Agnostic Gaussian Splatting through Multi-Scale Kernel Modeling

Reference 26

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Observation 3ff54484-b1f6-44fc-b5d6-4c4ac6680a44 · outbound

This paper cites Ani- matable neural radiance fields for modeling dynamic human bodies.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Ani- matable neural radiance fields for modeling dynamic human bodies

Reference 27

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Observation 055c3188-ef70-4fc7-b8c2-fc2b78c58191 · outbound

This paper cites D-nerf: Neural radiance fields for dynamic scenes.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images D-nerf: Neural radiance fields for dynamic scenes

Reference 28

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Observation 4630db1d-8f27-4e4b-b296-2d461d41a33c · outbound

This paper cites Pixelwise view selection for unstructured multi-view stereo.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Pixelwise view selection for unstructured multi-view stereo

Reference 29

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Observation 9e02bcaa-a352-4c15-97f0-81f8e0b32f82 · outbound

This paper cites High-quality mo- tion deblurring from a single image.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images High-quality mo- tion deblurring from a single image

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:57:40.141358Z

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Observation a899a747-36a4-47fe-b869-00078bd33dc4 · outbound

This paper cites Light field blind motion deblurring.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Light field blind motion deblurring

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:57:40.126124Z

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Observation c386f6e6-bad1-4e8a-909a-bda0aca246a4 · outbound

This paper cites Neuralrecon: Real-time coherent 3d reconstruc- tion from monocular video.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Neuralrecon: Real-time coherent 3d reconstruc- tion from monocular video

Reference 32

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Observation cfce97e0-0d11-4bf3-98d8-2f2f7bd00ec8 · outbound

This paper cites Non- rigid neural radiance fields: Reconstruction and novel view synthesis of a dynamic scene from monocular video.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Non- rigid neural radiance fields: Reconstruction and novel view synthesis of a dynamic scene from monocular video

Reference 33

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Observation 3d5bbd3b-6ddb-445e-967f-1c3a02f7f4f0 · outbound

This paper cites Sparsenerf: Distilling depth ranking for few-shot novel view synthesis.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Sparsenerf: Distilling depth ranking for few-shot novel view synthesis

Reference 34

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Observation 4d095a89-e5e7-4ce3-8218-cc60008d35a3 · outbound

This paper cites Neuris: Neural reconstruction of indoor scenes using normal priors.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Neuris: Neural reconstruction of indoor scenes using normal priors

Reference 35

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Observation 44e8dec5-a7cd-4022-afc2-84024b336d36 · outbound

This paper cites NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

Reference 36

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Observation 3d9e5a73-bce6-429c-8279-2709c4e630ee · outbound

This paper cites Bad-nerf: Bundle adjusted deblur neural radiance fields.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Bad-nerf: Bundle adjusted deblur neural radiance fields

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:57:40.060924Z

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Observation 44d0893c-09b2-42aa-94b3-518ec5a55a5d · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Image quality assessment: from error visibility to structural similarity

Reference 38

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Observation 7d10b837-31ee-453c-8af4-2035db17b6ae · outbound

This paper cites Hu- mannerf: Free-viewpoint rendering of moving people from monocular video.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Hu- mannerf: Free-viewpoint rendering of moving people from monocular video

Reference 39

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Observation 8fe20122-8cb3-467b-a934-168b24c27f02 · outbound

This paper cites Non-uniform deblurring for shaken images.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Non-uniform deblurring for shaken images

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:57:40.026266Z

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Observation edcd1159-5ebf-44ee-a558-4bb762b91de0 · outbound

This paper cites Dof-nerf: Depth-of-field meets neural radi- ance fields.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Dof-nerf: Depth-of-field meets neural radi- ance fields

Reference 41

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Observation 7537149d-97bc-4b9f-a99e-bf08c91ab8a7 · outbound

This paper cites Diffusionerf: Regularizing neural radiance fields with denoising diffu- sion models.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Diffusionerf: Regularizing neural radiance fields with denoising diffu- sion models

Reference 42

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Observation 4f01c15a-59ba-477e-8b78-7cb2d8667ed4 · outbound

This paper cites Freenerf: Im- proving few-shot neural rendering with free frequency reg- ularization.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Freenerf: Im- proving few-shot neural rendering with free frequency reg- ularization

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:57:39.986198Z

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Observation 02930ceb-3b25-4f62-bbd7-d6616da8d58b · outbound

This paper cites Differentiable surface splatting for point-based geometry processing.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Differentiable surface splatting for point-based geometry processing

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-11T10:57:39.617191Z

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Observation 12b7dca2-3976-4857-87b6-72ec1a674a53 · outbound

This paper cites Mip-splatting: Alias-free 3d gaussian splat- ting.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Mip-splatting: Alias-free 3d gaussian splat- ting

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T10:57:39.622170Z

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Observation 046eef4b-6de2-4d71-8c29-4f5ed771ae93 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images The unreasonable effectiveness of deep features as a perceptual metric

Reference 46

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This paper cites BAD-Gaussians: Bundle Adjusted Deblur Gaussian Splatting.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images BAD-Gaussians: Bundle Adjusted Deblur Gaussian Splatting

Reference 47

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Observation a744f275-73d8-4622-bf62-50cd4744f453 · outbound

This paper cites For coarse geom- etry in the early training stages, hθ is not trained during the first 2k iterations and begins training afterward.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images For coarse geom- etry in the early training stages, hθ is not trained during the first 2k iterations and begins training afterward

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:57:39.941108Z

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This paper cites acceptable CoC.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images acceptable CoC

Reference 49

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Observation d59350bf-371d-44d5-8e70-7659664fca97 · outbound

This paper cites an unresolved cited work.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Unresolved cited work

Reference 50

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Observation 3932da33-b737-4d6d-852f-b22960bda41b · outbound

This paper cites The first focuses on qualitative results related to the CoC scaling factor β, and the second evaluates the quantitative results based on the number of CoC Gaussian sets M.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images The first focuses on qualitative results related to the CoC scaling factor β, and the second evaluates the quantitative results based on the number of CoC Gaussian sets M

Reference 51

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Observation 57c0668e-00b5-4080-9c81-61372e69553c · outbound

This paper cites 8 and Fig.

CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images 8 and Fig

Reference 52

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CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Unresolved cited work

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CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images Unresolved cited work

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CoCoGaussian: Leveraging Circle of Confusion for Gaussian Splatting from Defocused Images 6, CoCoGaussian achieves com- parable resource consumption and training time while deliv- ering superior performance

Reference 3090

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