pith:A7XYV4UZ
SplAttN: Bridging 2D and 3D with Gaussian Soft Splatting and Attention for Point Cloud Completion
Differentiable Gaussian splatting replaces hard projection to prevent cross-modal entropy collapse in point cloud completion.
arxiv:2605.01466 v2 · 2026-05-02 · cs.CV · cs.LG
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\pithnumber{A7XYV4UZPFBH4QR7BSJGVJASHZ}
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Record completeness
Claims
SplAttN achieves state-of-the-art performance on PCN and ShapeNet-55/34. Counter-factual evaluation on KITTI reveals that while baselines degenerate into unimodal template retrievers insensitive to visual removal, SplAttN maintains a robust dependency on visual cues.
That the performance gains and KITTI robustness stem specifically from avoiding cross-modal entropy collapse via Gaussian splatting rather than from other architectural choices or training details not isolated in the reported experiments.
SplAttN replaces hard projection with Gaussian soft splatting to avoid cross-modal entropy collapse, achieving SOTA point cloud completion on PCN and ShapeNet while maintaining visual cue dependency on KITTI.
Receipt and verification
| First computed | 2026-05-22T01:04:04.040153Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
07ef8af29979427e423f0c926aa4123e76f20cdde83844e9de838fd5d15e2259
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/A7XYV4UZPFBH4QR7BSJGVJASHZ \
| 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: 07ef8af29979427e423f0c926aa4123e76f20cdde83844e9de838fd5d15e2259
Canonical record JSON
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