Pith Number

pith:6TQOLQGU

pith:2026:6TQOLQGU5HHKNYOH7XLBJRAPIA

not attested not anchored not stored refs resolved

Learning Dynamic Structural Specialization for Underwater Salient Object Detection

Bojian Zhang, Chenhui Wang, Fumin Zhang, Linan Deng, Lin Hong, Wenqi Ren, Xingchen Yang, Xin Wang, Yuning Cui, Yu Zhang

Dynamic structural specialization enhances underwater salient object detection by coordinating boundary and region features.

arxiv:2605.15535 v1 · 2026-05-15 · cs.CV

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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

DSS-USOD achieves superior performance on benchmark datasets and validates the practical effectiveness of DSS-USOD for underwater object inspection via real-world deployment on an underwater robot.

C2weakest assumption

That decomposing the shared base representation into a boundary-sensitive branch and a region-coherent branch, then using a spatial coordination module to regulate their contributions according to local structural context, will reliably correct inaccurate localization, fragmented regions, and coarse boundaries caused by underwater degradations.

C3one line summary

DSS-USOD decomposes underwater image features into boundary-sensitive and region-coherent branches with a spatial coordination module and cooperative supervision for improved salient object detection under degradations.

References

106 extracted · 106 resolved · 1 Pith anchors

[1] Perceptual inference, learning, and attention in a multi- sensory world, 2021

[2] A model of saliency-based visual attention for rapid scene analysis, 1998

[3] Global contrast based salient region detection, 2014

[4] Deep learning-based marine big data fusion for ocean environment monitoring: Towards shape optimization and salient objects detection, 2023

[5] Saliency ranking for benthic survey using underwater images, 2010

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-20T00:01:04.000542Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

f4e0e5c0d4e9cea6e1c7fdd614c40f403289469ec45968912a63e8a3248a44ba

Aliases

arxiv: 2605.15535 · arxiv_version: 2605.15535v1 · doi: 10.48550/arxiv.2605.15535 · pith_short_12: 6TQOLQGU5HHK · pith_short_16: 6TQOLQGU5HHKNYOH · pith_short_8: 6TQOLQGU

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/6TQOLQGU5HHKNYOH7XLBJRAPIA \
  | 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: f4e0e5c0d4e9cea6e1c7fdd614c40f403289469ec45968912a63e8a3248a44ba

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e46ecda7411368a793fc8d541af9ebe7bc4caeaa1b2c5b3fba05d0480262b4a3",
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-15T02:14:10Z",
    "title_canon_sha256": "0858444ef3ca5913e21974dab5c74f01da5717ca5ae67d1d7d8ac76bd31496a5"
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  "source": {
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    "kind": "arxiv",
    "version": 1
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}