Pith Number

pith:JFVI2FV2

pith:2026:JFVI2FV2KCVXMO52HS2MTWQVOG

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ClickRemoval: An Interactive Open-Source Tool for Object Removal in Diffusion Models

Ledun Zhang, Xinying Yao, Xufei Zhuang, Yatu Ji

Clicks alone let users remove objects from images in pretrained diffusion models

arxiv:2605.14461 v1 · 2026-05-14 · cs.CV

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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Claims

C1strongest claim

ClickRemoval localizes target objects and restores the background through self-attention modulation during denoising without additional training, hand-drawn masks, or text descriptions, achieving competitive results across quantitative metrics and user studies.

C2weakest assumption

That user clicks alone, combined with self-attention modulation in a pretrained Stable Diffusion model, are sufficient to accurately localize objects and produce natural background completions in complex scenes.

C3one line summary

ClickRemoval delivers click-driven object removal and background restoration in diffusion models through self-attention modulation without additional training or inputs.

References

15 extracted · 15 resolved · 0 Pith anchors

[1] Aditya Chandrasekar, Goirik Chakrabarty, Jai Bardhan, Ramya Hebbalaguppe, and Prathosh AP. 2024. Remove: A reference-free metric for object erasure. InPro- ceedings of the IEEE/CVF Conference on Compu 2024

[2] Nima Fathi, Amar Kumar, and Tal Arbel. 2025. Aura: A multi-modal medical agent for understanding, reasoning and annotation. InInternational Workshop on Agentic AI for Medicine. 105–114 2025

[3] Tariq Berrada Ifriqi, Adriana Romero-Soriano, Michal Drozdzal, Jakob Verbeek, and Karteek Alahari. 2025. Entropy Rectifying Guidance for Diffusion and Flow Models. InNeurIPS 2025-Thirty-ninth Conferen 2025

[4] Xuan Ju, Xian Liu, Xintao Wang, Yuxuan Bian, Ying Shan, and Qiang Xu. 2024. Brushnet: A plug-and-play image inpainting model with decomposed dual- branch diffusion. InEuropean Conference on Computer V 2024

[5] Markus Karmann and Onay Urfalioglu. 2025. Repurposing stable diffusion attention for training-free unsupervised interactive segmentation. InProceedings of the Computer Vision and Pattern Recognition C 2025

Receipt and verification

First computed	2026-05-17T23:39:06.776601Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

496a8d16ba50ab763bba3cb4c9da1571979ac47824c86f0b8b5117958e9c46f2

Aliases

arxiv: 2605.14461 · arxiv_version: 2605.14461v1 · doi: 10.48550/arxiv.2605.14461 · pith_short_12: JFVI2FV2KCVX · pith_short_16: JFVI2FV2KCVXMO52 · pith_short_8: JFVI2FV2

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/JFVI2FV2KCVXMO52HS2MTWQVOG \
  | 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: 496a8d16ba50ab763bba3cb4c9da1571979ac47824c86f0b8b5117958e9c46f2

Canonical record JSON

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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-05-14T06:56:53Z",
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