Pith Number

pith:YM42HKXD

pith:2025:YM42HKXD6S3LED2CNKOXBWOBDP

not attested not anchored not stored refs resolved

Streaming 4D Visual Geometry Transformer

Dong Zhuo, Jiahe Guo, Jie Zhou, Jiwen Lu, Wenzhao Zheng, Yuqi Wu

A causal streaming transformer reconstructs 3D geometry from video online by caching historical frame information.

arxiv:2507.11539 v2 · 2025-07-15 · cs.CV · cs.AI · cs.LG

Open paper page JSON Open Graph Bundle Merged state What is a Pith Number?

Record completeness

1 Bitcoin timestamp

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

Our model enhances inference speed in online scenarios while maintaining competitive performance, thereby facilitating scalable and interactive 3D vision systems.

C2weakest assumption

That knowledge distilled from the dense bidirectional VGGT model transfers effectively to the causal streaming architecture without losing critical spatial consistency over long sequences.

C3one line summary

A causal transformer with key-value caching and distillation from a bidirectional VGGT model enables efficient online 4D geometry reconstruction from videos.

References

16 extracted · 16 resolved · 8 Pith anchors

[1] ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data · arXiv:2111.08897

[2] Virtual KITTI 2 2001 · arXiv:2001.10773

[3] FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning · arXiv:2307.08691

[4] arXiv preprint arXiv:2412.06777 (2024)

[5] Stream3r: Scalable sequential 3d reconstruction with causal transformer

Formal links

2 machine-checked theorem links

Cited by

22 papers in Pith

PAGE-4D: VGGT-4D Perception via Disentangled Pose and Geometry Estimation

Co-Me: Confidence-Guided Token Merging for Visual Geometric Transformers

TTT3R: 3D Reconstruction as Test-Time Training

FastVGGT: Training-Free Acceleration of Visual Geometry Transformer

FrameVGGT: Geometry-Aligned Frame-Level Memory for Bounded Streaming VGGT

Receipt and verification

First computed	2026-05-17T23:38:49.862257Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

c339a3aae3f4b6b20f426a9d70d9c11be38c5f54bd00b4850515e5cdcbb6c6b7

Aliases

arxiv: 2507.11539 · arxiv_version: 2507.11539v2 · doi: 10.48550/arxiv.2507.11539 · pith_short_12: YM42HKXD6S3L · pith_short_16: YM42HKXD6S3LED2C · pith_short_8: YM42HKXD

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/YM42HKXD6S3LED2CNKOXBWOBDP \
  | 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: c339a3aae3f4b6b20f426a9d70d9c11be38c5f54bd00b4850515e5cdcbb6c6b7

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "4b1a119db23ba2a0d8f6e189c0b73963557d87527dc3dd2967be309373f91287",
    "cross_cats_sorted": [
      "cs.AI",
      "cs.LG"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2025-07-15T17:59:57Z",
    "title_canon_sha256": "a86349b28d8291141219b29bb327fe73eee0eb6d2c60c7b5fc5c6e1ca945a1a7"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2507.11539",
    "kind": "arxiv",
    "version": 2
  }
}