Pith Number

pith:YIOYEVFX

pith:2026:YIOYEVFXNNF366DXFWAKO4ARL7

not attested not anchored not stored refs resolved

Real2Sim: A Physics-driven and Editable Gaussian Splatting Framework for Autonomous Driving Scenes

Kaicong Huang, Ruimin Ke, Talha Azfar, Weisong Shi

A framework fuses 4D Gaussian Splatting with a physics solver to reconstruct and edit dynamic driving scenes while preserving realistic interactions.

arxiv:2605.13591 v1 · 2026-05-13 · cs.CV

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\pithnumber{YIOYEVFXNNF366DXFWAKO4ARL7}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Real2Sim explicitly reconstructs dynamic driving scenes as temporally continuous Gaussian primitives, supports instance-level editing, and simulates realistic object-object and object-environment interactions. This framework enables physics-aware, high-fidelity synthesis of diverse, editable scenarios, including challenging corner cases such as collisions and post-impact trajectories.

C2weakest assumption

That the differentiable MPM solver can be tightly coupled with 4D Gaussian Splatting without introducing visual artifacts, temporal inconsistencies, or loss of physical accuracy when applied to complex real-world driving data.

C3one line summary

Real2Sim reconstructs editable dynamic driving scenes as temporally continuous Gaussians integrated with a differentiable MPM physics solver for high-fidelity simulation of interactions and collisions.

References

27 extracted · 27 resolved · 1 Pith anchors

[1] Scalability in perception for autonomous driving: Waymo open dataset 2020

[2] Surfelgan: Synthesizing realistic sensor data for autonomous driving, 2020

[3] GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving 2025 · arXiv:2503.20523

[4] Nerf: Representing scenes as neural radiance fields for view synthesis 2021

[5] 3d gaussian splatting for real-time radiance field rendering 2023

Receipt and verification

First computed	2026-05-18T02:44:23.066189Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

c21d8254b76b4bbf78772d80a770115fd88c9eeed582dd655323a759ab665b60

Aliases

arxiv: 2605.13591 · arxiv_version: 2605.13591v1 · doi: 10.48550/arxiv.2605.13591 · pith_short_12: YIOYEVFXNNF3 · pith_short_16: YIOYEVFXNNF366DX · pith_short_8: YIOYEVFX

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/YIOYEVFXNNF366DXFWAKO4ARL7 \
  | 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: c21d8254b76b4bbf78772d80a770115fd88c9eeed582dd655323a759ab665b60

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4605331e552470134c3497372c690618e7b1cb591dc597b968a66c9f329de0f7",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-13T14:26:25Z",
    "title_canon_sha256": "d9dd2e621add870c13d2b5b636e864174df5e55b1d36a2c1a3d6fdab2fff61c1"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.13591",
    "kind": "arxiv",
    "version": 1
  }
}