Pith Number

pith:YYPWEKUC

pith:2026:YYPWEKUCSEGZRHQILEEPAQXQAG

not attested not anchored not stored refs pending

Frequency-Enhanced Diffusion Models: Curriculum-Guided Semantic Alignment for Zero-Shot Skeleton Action Recognition

Jingyu Pan, Yuxi Zhou, Zhengbo Zhang, Zhigang Tu, Zhiyu Lin

Frequency-aware diffusion models recover fine-grained motion details for zero-shot skeleton action recognition.

arxiv:2604.09063 v3 · 2026-04-10 · cs.CV · cs.AI

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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

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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

Our approach effectively recovers fine-grained motion details, achieving state-of-the-art performance on NTU RGB+D, PKU-MMD, and Kinetics-skeleton datasets.

C2weakest assumption

That the spectral bias of diffusion models is the primary bottleneck in zero-shot skeleton action recognition and that the three proposed modules (Semantic-Guided Spectral Residual Module, Timestep-Adaptive Spectral Loss, Curriculum-based Semantic Abstraction) directly correct it without introducing compensating errors or requiring dataset-specific tuning.

C3one line summary

FDSM recovers fine-grained motion details in zero-shot skeleton action recognition by integrating semantic-guided spectral residual, timestep-adaptive spectral loss, and curriculum-based semantic abstraction, reaching state-of-the-art on NTU RGB+D, PKU-MMD, and Kinetics-skeleton.

Receipt and verification

First computed	2026-06-02T02:04:17.289124Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

c61f622a82910d989e085908f042f001b8eee6e1e140a3a8516d9118d9efbac3

Aliases

arxiv: 2604.09063 · arxiv_version: 2604.09063v3 · doi: 10.48550/arxiv.2604.09063 · pith_short_12: YYPWEKUCSEGZ · pith_short_16: YYPWEKUCSEGZRHQI · pith_short_8: YYPWEKUC

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/YYPWEKUCSEGZRHQILEEPAQXQAG \
  | 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: c61f622a82910d989e085908f042f001b8eee6e1e140a3a8516d9118d9efbac3

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "1261fa2ca09e2716d7b799ac6f160c3645d934e2aa5dca469806d268579c4547",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-10T07:42:47Z",
    "title_canon_sha256": "b1f8588feb8d159c38ec6254bdf39e7e91a8116c4aca5732d31ad2b7c784d861"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.09063",
    "kind": "arxiv",
    "version": 3
  }
}