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Paper Citation Record · LEDGER

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video

As of 12 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 0 inbound Pith citation observations for arXiv:2509.08828.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.08828 v1

Coverage vector

measured 84 of 84 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T20:10:40.058587Z

measured 84 of 84 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

84 of 84 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8abeee68-56d7-4746-9c79-cd75a06aa8f8 · outbound

This paper cites Large steps in cloth sim- ulation.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Large steps in cloth sim- ulation

Reference 1

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Observation 45f75553-cf7f-4189-b14d-130278c7d20c · outbound

This paper cites Shape-from-template.IEEE TPAMI, 37(10):2099–2118, 2015.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Shape-from-template.IEEE TPAMI, 37(10):2099–2118, 2015

Reference 2

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Observation 5c436f5f-9b27-4c16-ae4b-898fef505f87 · outbound

This paper cites PBNS: Physically Based Neural Simulator for Unsupervised Garment Pose Space Deformation.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video PBNS: Physically Based Neural Simulator for Unsupervised Garment Pose Space Deformation

Reference 3

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Observation ed9fa25a-427d-4e44-ad42-c89cd04b6b32 · outbound

This paper cites Neu- ral cloth simulation.ACM TOG, 41, 2022.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Neu- ral cloth simulation.ACM TOG, 41, 2022

Reference 4

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Observation dbdcf500-7d63-41e8-92b9-f9e7bf4dc1e3 · outbound

This paper cites Lensch, and Jan Kautz.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Lensch, and Jan Kautz

Reference 5

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Observation b0c4967d-bb39-49bc-995b-2435a8b719fd · outbound

This paper cites Bregler, A.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Bregler, A

Reference 6

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Observation 6deaf6ba-3217-4a11-a46e-da5bf8ac48a7 · outbound

This paper cites The isowarp: the template-based visual geometry of isometric surfaces.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video The isowarp: the template-based visual geometry of isometric surfaces

Reference 7

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Observation 426ea4a9-179a-40c3-bb62-cb5be9f20c55 · outbound

This paper cites Neural ordinary differential equa- tions.Advances in neural information processing systems, 31, 2018.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Neural ordinary differential equa- tions.Advances in neural information processing systems, 31, 2018

Reference 8

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Observation a51299e9-fa06-4f78-834b-ab52f50502e2 · outbound

This paper cites an unresolved cited work.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Unresolved cited work

Reference 9

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Observation 03d86b16-15e7-4419-b560-8fe514dad7c9 · outbound

This paper cites Efficient simulation of knitted cloth using persistent contacts.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Efficient simulation of knitted cloth using persistent contacts

Reference 10

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Observation fcdce344-9100-48ef-98ab-0f79c0701814 · outbound

This paper cites Neural parametric gaussians for monocular non-rigid object reconstruction.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Neural parametric gaussians for monocular non-rigid object reconstruction

Reference 11

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Observation 279abfbc-ad19-4099-ba95-628ccb72eaa0 · outbound

This paper cites Drapenet: Garment generation and self- supervised draping.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Drapenet: Garment generation and self- supervised draping

Reference 12

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Observation 8c81624d-faaf-47e8-8076-ce66ec38272a · outbound

This paper cites Single-image svbrdf cap- ture with a rendering-aware deep network.ACM Trans.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Single-image svbrdf cap- ture with a rendering-aware deep network.ACM Trans

Reference 13

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Observation a9ee053d-a10b-42ac-b553-aa6601bb6cdd · outbound

This paper cites Diffpd: Dif- ferentiable projective dynamics.ACM TOG, 41(2), 2021.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Diffpd: Dif- ferentiable projective dynamics.ACM TOG, 41(2), 2021

Reference 14

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Observation 6c17f677-e58a-47ef-8c0b-0af6c3f145be · outbound

This paper cites Learning-based bending stiffness parameter estima- tion by a drape tester.ACM TOG, 41(6), 2022.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Learning-based bending stiffness parameter estima- tion by a drape tester.ACM TOG, 41(6), 2022

Reference 15

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Observation 0c687e8f-a065-48d8-8ebf-5223b43d56f8 · outbound

This paper cites Texture-generic deep shape-from-template.IEEE Access, 9:75211–75230,.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Texture-generic deep shape-from-template.IEEE Access, 9:75211–75230,

Reference 16

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Observation 4700f620-3798-4712-a82a-f70cb6643aa3 · outbound

This paper cites Deep inverse rendering for high-resolution svbrdf estimation from an arbitrary number of images.ACM Trans.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Deep inverse rendering for high-resolution svbrdf estimation from an arbitrary number of images.ACM Trans

Reference 17

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Observation 81d7f6e0-e59b-48a7-83f1-6d2ff3399f13 · outbound

This paper cites Modeling the dy- namics of pde systems with physics-constrained deep auto- regressive networks.Journal of Computational Physics, 403: 109056, 2020.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Modeling the dy- namics of pde systems with physics-constrained deep auto- regressive networks.Journal of Computational Physics, 403: 109056, 2020

Reference 18

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Observation 5a4c1cd8-15bd-4d0e-b7ce-19c5f6348f41 · outbound

This paper cites Hdm-net: Monocular non-rigid 3d recon- struction with learned deformation model.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Hdm-net: Monocular non-rigid 3d recon- struction with learned deformation model

Reference 19

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Observation e7af1a5d-e42e-48a2-bf7f-b409d068669f · outbound

This paper cites Fine-grained dif- ferentiable physics: a yarn-level model for fabrics.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Fine-grained dif- ferentiable physics: a yarn-level model for fabrics

Reference 20

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Observation 6d01138e-9bba-4345-96e7-4c0629f609bc · outbound

This paper cites Black, and Otmar Hilliges.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Black, and Otmar Hilliges

Reference 21

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Observation 94412cf8-0dc7-4c0e-aae5-28c20a5cf426 · outbound

This paper cites Real-time geometry, albedo, and mo- tion reconstruction using a single rgb-d camera.ACM Trans.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Real-time geometry, albedo, and mo- tion reconstruction using a single rgb-d camera.ACM Trans

Reference 22

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Observation dff53a79-a5ea-466a-9fcb-b6ccbe511222 · outbound

This paper cites an unresolved cited work.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Unresolved cited work

Reference 23

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Observation 56a7c9db-b46d-4a36-b8f5-90407850aa5f · outbound

This paper cites Shape, light, and material decomposition from images using monte carlo rendering and denoising.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Shape, light, and material decomposition from images using monte carlo rendering and denoising

Reference 24

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Observation 5a476399-1a24-422c-9c4f-e42d746b9e64 · outbound

This paper cites Diff- taichi: Differentiable programming for physical simulation.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Diff- taichi: Differentiable programming for physical simulation

Reference 25

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Observation e3f4d7c9-042a-496b-ac42-6621eb83ebab · outbound

This paper cites Estimating cloth simu- lation parameters from a static drape using neural networks.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Estimating cloth simu- lation parameters from a static drape using neural networks

Reference 26

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Observation eb978e47-9082-4d63-8602-a46546ccdb01 · outbound

This paper cites In CVPR, pages 3948–3958, 2022.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video In CVPR, pages 3948–3958, 2022

Reference 27

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Observation aa648e54-9eaf-464a-b01d-50bbafb2f623 · outbound

This paper cites NeuralClothSim: Neural Deformation Fields Meet the Thin Shell Theory.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video NeuralClothSim: Neural Deformation Fields Meet the Thin Shell Theory

Reference 28

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Observation 91e52eb1-8f64-4341-994f-653ede2dc5f6 · outbound

This paper cites Uni- fied shape and appearance reconstruction with joint camera parameter refinement.Graphical Models, 129, 2023.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Uni- fied shape and appearance reconstruction with joint camera parameter refinement.Graphical Models, 129, 2023

Reference 29

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Observation 4b4fdc77-4756-43ba-ba2b-0f3650114f8e · outbound

This paper cites Rosa: Reconstructing object shape and appearance textures by adaptive detail transfer.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Rosa: Reconstructing object shape and appearance textures by adaptive detail transfer

Reference 30

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Observation 90a26851-82ad-44ed-93e2-096632fb6cb0 · outbound

This paper cites Deep svbrdf acquisition and modelling: A survey.Computer Graphics Forum, 43(6):e15199, 2024.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Deep svbrdf acquisition and modelling: A survey.Computer Graphics Forum, 43(6):e15199, 2024

Reference 31

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Observation 44673b68-2dca-45e9-a712-5df222d64469 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick

Reference 32

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Observation c143de96-b834-4352-8595-775a4fad7e26 · outbound

This paper cites Modular primitives for high-performance differentiable rendering.ACM TOG, 39 (6), 2020.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Modular primitives for high-performance differentiable rendering.ACM TOG, 39 (6), 2020

Reference 33

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Observation 151b6d17-543c-4a17-ad0b-cedcc254d104 · outbound

This paper cites Mod- eling surface appearance from a single photograph using self-augmented convolutional neural networks.ACM Trans.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Mod- eling surface appearance from a single photograph using self-augmented convolutional neural networks.ACM Trans

Reference 34

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Observation 91035896-5203-4711-b77c-66aba29e16e9 · outbound

This paper cites Diffcloth: Differentiable cloth simulation with dry frictional contact.ACM TOG, 42(1), 2022.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Diffcloth: Differentiable cloth simulation with dry frictional contact.ACM TOG, 42(1), 2022

Reference 35

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Observation 993366a0-fefb-4bb6-98ce-c7916f07d693 · outbound

This paper cites Learning to recon- struct shape and spatially-varying reflectance from a single image.ACM Trans.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Learning to recon- struct shape and spatially-varying reflectance from a single image.ACM Trans

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Observation 27273b9c-67e9-45b2-bb4a-a549e2fa9366 · outbound

This paper cites Differen- tiable cloth simulation for inverse problems.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Differen- tiable cloth simulation for inverse problems

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source=pdf_text observed=2026-08-04T20:10:39.875921Z digest=sha256:5662298a5ddbc3c4c23ec83aad0ea9514fb70117a6a19207281069dec58bff7d

Observation f5c4ccab-c0a6-439f-90f9-ce6ea89aa802 · outbound

This paper cites an unresolved cited work.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Unresolved cited work

Reference 38

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source=pdf_text observed=2026-08-04T20:10:39.879773Z digest=sha256:e4e66ae85fe8433bd3f21934dbd72af4692de5c78469f924c6a376557395ea5e

Observation e7315098-1582-41a1-9082-d089a5352b0d · outbound

This paper cites Better Together: Joint Reasoning for Non-rigid 3D Reconstruction with Specularities and Shading.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Better Together: Joint Reasoning for Non-rigid 3D Reconstruction with Specularities and Shading

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Observation b262624c-4dad-4adb-aa1f-30a5a283a91e · outbound

This paper cites Warp: A high-performance python frame- work for gpu simulation and graphics.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Warp: A high-performance python frame- work for gpu simulation and graphics

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source=pdf_text observed=2026-08-04T20:10:39.887713Z digest=sha256:6943cd577affdaef3be17beb34eb3da58e792d6351ba26ba30a932b4c2aeccf3

Observation 1d894de4-4918-434f-9589-a8be2179f661 · outbound

This paper cites Physical simulation layer for accurate 3d modeling.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Physical simulation layer for accurate 3d modeling

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source=pdf_text observed=2026-08-04T20:10:39.891457Z digest=sha256:3b698cef127a39bf420f76bca4ed5dbd5e50935b5ea883eb77f81cd0384c2738

Observation 9c06ea82-e20a-45ad-bf08-5fb8a201285d · outbound

This paper cites Extracting Triangular 3D Models, Materials, and Light- ing From Images.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Extracting Triangular 3D Models, Materials, and Light- ing From Images

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source=pdf_text observed=2026-08-04T20:10:39.895530Z digest=sha256:8676649ad15adaea249e946e6a73a7aa2d7d02a1fb921e1d539392737ba7159c

Observation ec918873-c0e0-4bbe-8218-0729e4c78997 · outbound

This paper cites an unresolved cited work.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Unresolved cited work

Reference 43

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source=pdf_text observed=2026-08-04T20:10:39.900263Z digest=sha256:f354d4badcfbd26a925afc68446a6e2878e023de0115a5e3d9aa78d513274319

Observation 447adeb7-e72a-4c4b-9095-84a21b9549ad · outbound

This paper cites Local non-rigid structure-from-motion from diffeomorphic map- pings.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Local non-rigid structure-from-motion from diffeomorphic map- pings

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source=pdf_text observed=2026-08-04T20:10:39.904336Z digest=sha256:61ed9f20505a2b9cc62eba2e50afed2b77ee7bee503285c57841fe218f94d3e4

Observation d7747664-d797-4712-bfbe-2d71cf203ae2 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Pytorch: An imperative style, high-performance deep learning library

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source=pdf_text observed=2026-08-04T20:10:39.907945Z digest=sha256:12d205d7d0a0c2012ee14accd605bdd2b2b8d06a43479172be153a54c9b4e09e

Observation 6c8d0af4-4273-4566-8a96-5c3a6b5db2e5 · outbound

This paper cites Learning mesh-based simulation with graph networks.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Learning mesh-based simulation with graph networks

Reference 46

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source=pdf_text observed=2026-08-04T20:10:39.911778Z digest=sha256:2b4b6078b47dfaeb91877d62fc6b675f848e0427063c3cd42f2fe4c0421deb57

Observation ab3b5200-d4e6-49dc-94a2-2e5d1f87d467 · outbound

This paper cites Geometry-aware network for non-rigid shape prediction from a single view.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Geometry-aware network for non-rigid shape prediction from a single view

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source=pdf_text observed=2026-08-04T20:10:39.915691Z digest=sha256:658f5b1b3154d99bdb83d6a140fdb28d094f5499cc7536d22259f6181043e0a7

Observation 510051ef-2670-4140-b484-2a6812171cb6 · outbound

This paper cites Scalable differentiable physics for learning and control.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Scalable differentiable physics for learning and control

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source=pdf_text observed=2026-08-04T20:10:39.919354Z digest=sha256:14b11da8e2246ee04a9e8358241ec1b02393361f20146441433b4beff2726564

Observation 2e1dde73-530f-4843-b0c6-2cdb76ca03d9 · outbound

This paper cites an unresolved cited work.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Unresolved cited work

Reference 49

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source=pdf_text observed=2026-08-04T20:10:39.922928Z digest=sha256:218a46d1cc677fa46f8a821d2ae8858180f7a9bf69e989d21ee574c5974a0ab2

Observation 751dfdad-d5f0-4df6-ab30-150f9b504002 · outbound

This paper cites Accelerating 3d deep learning with pytorch3d, 2020.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Accelerating 3d deep learning with pytorch3d, 2020

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source=pdf_text observed=2026-08-04T20:10:39.926767Z digest=sha256:6cc8d5911dc419630dfca3adc12003be9e1b074e8f50b530feefbc8b1986539c

Observation dc2ab998-dbbb-46a8-af13-01a7d1a8eec5 · outbound

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

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video SAM 2: Segment Anything in Images and Videos

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source=pdf_text observed=2026-08-04T20:10:39.930497Z digest=sha256:376cc9b39228d211c330076320ca70ecf1c1d4ead94e77a7aea0604256c7fb55

Observation 4ea9ffec-68bf-4556-89fb-be779565f2c2 · outbound

This paper cites How will it drape like? capturing fabric mechanics from depth images.Computer Graphics Forum, 42(2):149–160, 2023.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video How will it drape like? capturing fabric mechanics from depth images.Computer Graphics Forum, 42(2):149–160, 2023

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source=pdf_text observed=2026-08-04T20:10:39.935480Z digest=sha256:1c7686a1cfe8335bbb08b0e9cde7008cd68fca931e3074d3077bf490727e5330

Observation ac3795db-c29b-4d2c-90d5-5e25487e4954 · outbound

This paper cites Gaussian Garments: Reconstructing Simulation-Ready Clothing with Photorealistic Appearance from Multi-View Video.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Gaussian Garments: Reconstructing Simulation-Ready Clothing with Photorealistic Appearance from Multi-View Video

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source=pdf_text observed=2026-08-04T20:10:39.939235Z digest=sha256:a7ddecd05f082abed88c93372e56a26a87bfb588783337292b0a927c9a2518d4

Observation 3d96ee9b-1582-4346-a6d6-83718dd88129 · outbound

This paper cites De- formable surface tracking ambiguities.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video De- formable surface tracking ambiguities

Reference 54

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source=pdf_text observed=2026-08-04T20:10:39.943497Z digest=sha256:262d495e08f5ba76474681e13e3efa3d4b6918e1e33f7f5a93e8a48d2c6112cd

Observation c6c2df9a-763f-4a92-89a7-da5f4cec64ba · outbound

This paper cites Otaduy, and Dan Casas.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Otaduy, and Dan Casas

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source=pdf_text observed=2026-08-04T20:10:39.947076Z digest=sha256:0516c7b9bfda497ea2f19ee94bcaf8795349ea477c12695c67303789f9dab7d5

Observation c1fca0da-75b9-459e-a380-813695b18d65 · outbound

This paper cites Autoclip: Adaptive gradient clipping for source separation networks.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Autoclip: Adaptive gradient clipping for source separation networks

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source=pdf_text observed=2026-08-04T20:10:39.950644Z digest=sha256:e1317e5bab0002f654ad05800b6e90a6eb563242a52e093545a1dc199f9f5020

Observation db551e07-4870-4927-acbe-943c5a11f90c · outbound

This paper cites Towards multi- layered 3d garments animation.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Towards multi- layered 3d garments animation

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source=pdf_text observed=2026-08-04T20:10:39.954202Z digest=sha256:ceb282bedab215569748d233dcba28e846c1576814374e791701bbe0a9a5ca9e

Observation 938b0742-2c77-4672-bca2-b1c9db8e83cd · outbound

This paper cites Robusft: Ro- bust real-time shape-from-template, a c++ library.Image and Vision Computing, 141:104867, 2024.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Robusft: Ro- bust real-time shape-from-template, a c++ library.Image and Vision Computing, 141:104867, 2024

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source=pdf_text observed=2026-08-04T20:10:39.957960Z digest=sha256:cd71b8295dd3ef6e383a1475b3d0a6d19c85dbc491d55b1cd915d3a43f54c192

Observation 3dfab2b4-9dad-4cdf-8189-aae2af9fddd9 · outbound

This paper cites Ismo-gan: Adversarial learning for monoc- ular non-rigid 3d reconstruction.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Ismo-gan: Adversarial learning for monoc- ular non-rigid 3d reconstruction

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source=pdf_text observed=2026-08-04T20:10:39.961565Z digest=sha256:4603d4069fc5648779d5e6616eb68f6a3e5f2378d154d5a8212bd940fdf57f51

Observation c10fd565-1aaa-43c7-8fd6-9a310c1e11f6 · outbound

This paper cites Neural dense non- rigid structure from motion with latent space constraints.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Neural dense non- rigid structure from motion with latent space constraints

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source=pdf_text observed=2026-08-04T20:10:39.965443Z digest=sha256:8c401bedfc78d41b949509d3541746d27f7a11329c7187d481c221205babc7a8

Observation 879e7578-c219-4503-bff6-b7ae7a2dcdd5 · outbound

This paper cites Sobolevfusion: 3d reconstruction of scenes undergoing free non-rigid motion.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Sobolevfusion: 3d reconstruction of scenes undergoing free non-rigid motion

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source=pdf_text observed=2026-08-04T20:10:39.969161Z digest=sha256:4c96d441b8b3552f586ba4ec3364d97cd8c51ef4c34887baeacdcc5105c4995b

Observation ab371786-e661-4e9b-8c52-9f769391d23a · outbound

This paper cites Physics- guided Shape-from-Template: Monocular Video Percep- tion through Neural Surrogate Models.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Physics- guided Shape-from-Template: Monocular Video Percep- tion through Neural Surrogate Models

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source=pdf_text observed=2026-08-04T20:10:39.972818Z digest=sha256:7606e3222cfb767b24a7785078ce27aed737a9d7c48bfa89f830989f2f560975

Observation 2ae4e25d-f8d7-45d4-ace7-14f5cb24816b · outbound

This paper cites Caphy: Cap- turing physical properties for animatable human avatars.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Caphy: Cap- turing physical properties for animatable human avatars

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source=pdf_text observed=2026-08-04T20:10:39.976868Z digest=sha256:db96d491298eb2d822bf1dbec06985dad218f9aef5bfd90678ac6d3717182815

Observation d473d919-d945-4ee0-bba5-07bf94f6b707 · outbound

This paper cites Sullivan.Curves of Finite Total Curvature, pages 137–161.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Sullivan.Curves of Finite Total Curvature, pages 137–161

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source=pdf_text observed=2026-08-04T20:10:39.980918Z digest=sha256:380f9d3bebe5c593e15e08cfadf1e2bab1fbd04f3c10d2007f99a338895f4685

Observation 82698288-ce27-4585-b30e-04d1300ba91b · outbound

This paper cites Dif- fcloud: Real-to-sim from point clouds with differentiable simulation and rendering of deformable objects.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Dif- fcloud: Real-to-sim from point clouds with differentiable simulation and rendering of deformable objects

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source=pdf_text observed=2026-08-04T20:10:39.984627Z digest=sha256:ef72c3fe74e954c72ddfe79927eeacf8f67f4aa2741c69e79f25495dea9b283f

Observation 00eaf0c5-4c82-4418-b038-6af4b90d37af · outbound

This paper cites Improved shape-from-template method with perspective space constraints for disappearing features.Complex & Intelligent Systems, pages 1–14, 2024.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Improved shape-from-template method with perspective space constraints for disappearing features.Complex & Intelligent Systems, pages 1–14, 2024

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source=pdf_text observed=2026-08-04T20:10:39.988250Z digest=sha256:7c26f073fc5aec591ab47908ec69462608b35fbd91f45710e554c098f973b758

Observation 3d6639e1-3ba6-4543-bf9c-07ec446139ba · outbound

This paper cites State of the art in dense monocular non-rigid 3d reconstruction.Comput.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video State of the art in dense monocular non-rigid 3d reconstruction.Comput

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source=pdf_text observed=2026-08-04T20:10:39.992492Z digest=sha256:ade9476910f9e33a049b0dfd2f5ec2bb5f6402b60a17a76983e304e19f6e9d03

Observation 86e3ecfd-e6c5-42eb-97fc-ae79eba4592b · outbound

This paper cites Huang, Omid Taheri, Michael J.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Huang, Omid Taheri, Michael J

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source=pdf_text observed=2026-08-04T20:10:39.998117Z digest=sha256:9a1b966097a4a16047481bb7397f3c545816c3398a4a940e01c9b784478c25a6

Observation 3119b876-d398-4c57-874b-ae7d92555a69 · outbound

This paper cites Learning Incompressible Fluid Dynamics from Scratch -- Towards Fast, Differentiable Fluid Models that Generalize.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Learning Incompressible Fluid Dynamics from Scratch -- Towards Fast, Differentiable Fluid Models that Generalize

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source=pdf_text observed=2026-08-04T20:10:40.001771Z digest=sha256:5d053df4576f0eed48194bc3c52c98c2f94961e81f93eee5e88b558b443cbc63

Observation 31b6093f-6bb6-4d10-98b2-0356756ce782 · outbound

This paper cites Metamizer: a versatile neural optimizer for fast and accurate physics simulations.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Metamizer: a versatile neural optimizer for fast and accurate physics simulations

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source=pdf_text observed=2026-08-04T20:10:40.005735Z digest=sha256:d69a1151ccd415a9454b1ec926a0373595886641caa7bc9dbd62782e95af361d

Observation 22aab2ff-faee-4988-b7ca-7d12b35f39df · outbound

This paper cites Interdiff: Generating 3d human-object interactions with physics-informed diffusion.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Interdiff: Generating 3d human-object interactions with physics-informed diffusion

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source=pdf_text observed=2026-08-04T20:10:40.009454Z digest=sha256:8fcc76647717d54bd90cc9ba5626d35af44e397a1b8c1a01804f129f9c59eb31

Observation 23922d16-0783-46e7-ae63-459c5eba36c0 · outbound

This paper cites Zhang, Zachary Manchester, and Deva Ramanan.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Zhang, Zachary Manchester, and Deva Ramanan

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source=pdf_text observed=2026-08-04T20:10:40.012985Z digest=sha256:99d3609bc4705d419e30aa714cda304c5c090d1286b33e6eb67001f6893914ef

Observation 8dfbd5d1-a780-4917-8364-f5a41da03cb6 · outbound

This paper cites an unresolved cited work.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Unresolved cited work

Reference 73

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Observation 5a2c8eec-6754-45c6-a160-f0478f15f213 · outbound

This paper cites Single image surface appearance modeling with self- augmented cnns and inexact supervision.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Single image surface appearance modeling with self- augmented cnns and inexact supervision

Reference 74

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Observation 616568cf-baf9-4d66-8a1c-4ef969447ac6 · outbound

This paper cites Deep reflectance scanning: Recovering spatially-varying mate- rial appearance from a flash-lit video sequence.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Deep reflectance scanning: Recovering spatially-varying mate- rial appearance from a flash-lit video sequence

Reference 75

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Observation a4293247-22fd-49fd-8a82-330b7cf54825 · outbound

This paper cites an unresolved cited work.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Unresolved cited work

Reference 76

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Observation 283511d1-cc51-4918-bea1-e1e4680ad739 · outbound

This paper cites Physdiff: Physics-guided human motion diffusion model.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Physdiff: Physics-guided human motion diffusion model

Reference 77

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Observation ae4e306c-e147-4f3b-8a43-b2a93b26fcd7 · outbound

This paper cites Recent trends in 3d reconstruction of general non-rigid scenes.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Recent trends in 3d reconstruction of general non-rigid scenes

Reference 78

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Observation 771bc34e-e7ac-4987-95a0-25328344d310 · outbound

This paper cites Iron: Inverse rendering by optimizing neural sdfs and materials from photometric images.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Iron: Inverse rendering by optimizing neural sdfs and materials from photometric images

Reference 79

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Observation 174a2b0c-5ae2-4160-aa9d-0e975ec688dd · outbound

This paper cites Physavatar: Learning the physics of dressed 3d avatars from visual observations.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Physavatar: Learning the physics of dressed 3d avatars from visual observations

Reference 80

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Observation 49db79b0-c868-4c51-97e0-fa462eb844c6 · outbound

This paper cites Adversarial single-image svbrdf estimation with hybrid training.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Adversarial single-image svbrdf estimation with hybrid training

Reference 81

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Observation acd4c994-0a9a-457b-9068-c2911486a78d · outbound

This paper cites Numerical Integration Scheme For simulation, we discretize the time into constant steps of∆t= 5 msresulting in all time-dependent quantities to be discretized accordingly,e.g.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Numerical Integration Scheme For simulation, we discretize the time into constant steps of∆t= 5 msresulting in all time-dependent quantities to be discretized accordingly,e.g

Reference 82

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Observation 42a67235-3f78-478a-9cd7-3a4163a0bad2 · outbound

This paper cites Simulation Scheme As a consequence of the spatial discretization into discrete vertices, the energy terms dependent not only on a single vertex but also on neighboring vertices.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Simulation Scheme As a consequence of the spatial discretization into discrete vertices, the energy terms dependent not only on a single vertex but also on neighboring vertices

Reference 83

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Observation 9ff91b3f-257c-46e4-bac1-832ca4944969 · outbound

This paper cites an unresolved cited work.

SAFT: Shape and Appearance of Fabrics from Template via Differentiable Physical Simulations from Monocular Video Unresolved cited work

Reference 84

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