Pith Number

pith:XL74VOAF

pith:2024:XL74VOAFGBNFUP7KIUE6RRVDQH

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On Efficient Variants of Segment Anything Model: A Survey

Heng Tao Shen, Jun Liu, Ping Hu, Xiaofeng Zhu, Xiaorui Sun

This survey reviews acceleration strategies for the Segment Anything Model and benchmarks their efficiency-accuracy trade-offs on multiple hardware platforms.

arxiv:2410.04960 v6 · 2024-10-07 · cs.CV

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Claims

C1strongest claim

This survey provides the first comprehensive review of efficient SAM variants. We begin by exploring the motivations driving this research. We then present core techniques used in SAM and model acceleration. This is followed by a detailed exploration of SAM acceleration strategies, categorized by approach, and a discussion of several future research directions. Finally, we offer a unified and extensive evaluation of these methods across various hardware, assessing their efficiency and accuracy on representative benchmarks, and providing a clear comparison of their overall performance.

C2weakest assumption

The review assumes that the authors have identified and fairly categorized all major efficient SAM variants without significant selection bias and that the chosen benchmarks and hardware platforms are representative of real deployment scenarios.

C3one line summary

A survey that reviews efficient variants of the Segment Anything Model, categorizes acceleration strategies, and provides a unified hardware evaluation on benchmarks.

Cited by

1 paper in Pith

LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation

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First computed	2026-06-05T01:15:11.928001Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

baffcab805305a5a3fea4509e8c6a381dff0223095c7e606b5db5a1d85ca0202

Aliases

arxiv: 2410.04960 · arxiv_version: 2410.04960v6 · doi: 10.48550/arxiv.2410.04960 · pith_short_12: XL74VOAFGBNF · pith_short_16: XL74VOAFGBNFUP7K · pith_short_8: XL74VOAF

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/XL74VOAFGBNFUP7KIUE6RRVDQH \
  | 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: baffcab805305a5a3fea4509e8c6a381dff0223095c7e606b5db5a1d85ca0202

Canonical record JSON

{
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    "abstract_canon_sha256": "8f0538c6b5456264439bf2b435d5326f609281d52d702ef921a1b3006142747b",
    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2024-10-07T11:59:54Z",
    "title_canon_sha256": "e5610b6162af451877d27b8635015b21970b0ebb49bc94390388fbb516939d2e"
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    "kind": "arxiv",
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