pith:WHQVFGXV
Rendering-Aware Sparse Sampling for BRDF Acquisition
A sampler optimized via gradients from a fixed hypernetwork reconstructor selects sparse BRDF directions that improve low-budget material reconstruction.
arxiv:2604.26740 v2 · 2026-04-29 · cs.CV · cs.GR
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\pithnumber{WHQVFGXV4PHASWPAMJ6IKU45OI}
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Record completeness
Claims
Experiments on the MERL dataset show that the proposed sampler improves low-budget reconstruction quality at 8 and 16 measurements compared with neural reconstruction baselines, while PCA-based methods remain strong at larger budgets.
That a pretrained hypernetwork reconstructor fixed during sampler training will produce gradients that reliably identify measurement directions informative for unseen materials outside the training distribution.
A sampler network learns to select informative sparse BRDF measurement directions by optimizing against a fixed pretrained hypernetwork reconstructor and differentiable renderer, improving low-budget reconstruction on the MERL dataset.
Receipt and verification
| First computed | 2026-05-26T01:03:31.345502Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
b1e1529af5e3ce0959e0627c85539d722b9bffd6c678c9d9ac21d2ff65f95ec5
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/WHQVFGXV4PHASWPAMJ6IKU45OI \
| 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: b1e1529af5e3ce0959e0627c85539d722b9bffd6c678c9d9ac21d2ff65f95ec5
Canonical record JSON
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