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pith:M7465QCI

pith:2025:M7465QCI4M2X5WHZKXBOTJFSAL
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G-SHARP: Gaussian Surgical Hardware Accelerated Real-time Pipeline

Aravind S. Kumar, Filippo Filicori, Javier G. Tejero, Mahdi Azizian, Ruilong Li, Sean D. Huver, Vishwesh Nath

G-SHARP is the first surgical reconstruction pipeline built natively on the open GSplat Gaussian rasterizer to support real-time modeling of deformable tissue.

arxiv:2512.02482 v2 · 2025-12-02 · cs.CV

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Claims

C1strongest claim

G-SHARP is the first surgical pipeline built natively on the GSplat (Apache-2.0) differentiable Gaussian rasterizer, enabling principled deformation modeling, robust occlusion handling, and high-fidelity reconstructions on the EndoNeRF pulling benchmark with strong speed-accuracy trade-offs suitable for intra-operative use.

C2weakest assumption

That native integration with the commercial GSplat library plus the added deformation and occlusion modules will deliver both the claimed reconstruction quality and real-time performance on actual surgical hardware without requiring non-commercial modifications or extensive per-case tuning.

C3one line summary

G-SHARP is a Gaussian splatting pipeline for real-time deformable tissue reconstruction in surgery, built on the open GSplat rasterizer and deployed via Holoscan on NVIDIA edge hardware with claimed state-of-the-art results on the EndoNeRF benchmark.

References

26 extracted · 26 resolved · 0 Pith anchors

[1] Neural rendering for stereo 3d reconstruction of deformable tissues 2022
[2] Efficient endonerf reconstruction and surgical guidance.PMCID: PMC11098936, 2024 2024
[3] Endogs: Gaussian splatting for real-time endoscopic soft tissue reconstruction.arXiv:2401.11535, 2024 2024
[4] Endogaussian: Real-time gaussian splat- ting for dynamic endoscopic scene reconstruction 2024
[5] Endo-4dgs: Endoscopic monoc- ular scene reconstruction with 4d gaussian splatting 2024

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Receipt and verification
First computed 2026-05-17T23:39:16.951801Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

67f9eec048e3357ed8f955c2e9a4b202f765deb895141362c9c105cb7306bc3f

Aliases

arxiv: 2512.02482 · arxiv_version: 2512.02482v2 · doi: 10.48550/arxiv.2512.02482 · pith_short_12: M7465QCI4M2X · pith_short_16: M7465QCI4M2X5WHZ · pith_short_8: M7465QCI
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/M7465QCI4M2X5WHZKXBOTJFSAL \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 67f9eec048e3357ed8f955c2e9a4b202f765deb895141362c9c105cb7306bc3f
Canonical record JSON
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2025-12-02T07:18:46Z",
    "title_canon_sha256": "8201c61d57e08e3883e9c9c7e72e9bf8ec071613f72b631edf0c73cec9d272a0"
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