{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T09:11:54Z","timestamp":1789117914212,"version":"build-2803163510"},"publisher-location":"Cham","reference-count":39,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032371669","type":"print"},{"value":"9783032371676","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-37167-6_6","type":"book-chapter","created":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T08:48:57Z","timestamp":1789116537000},"page":"96-113","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["LayerVerse: Finding the\u00a0Sweet Spot for\u00a0KV-Injection in\u00a0Training-Free Image Editing"],"prefix":"10.1007","author":[{"given":"Mikhail","family":"Zhirnov","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arsen","family":"Kuzhamuratov","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrey","family":"Kuznetsov","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ivan","family":"Oseledets","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Konstantin","family":"Sobolev","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,12]]},"reference":[{"key":"6_CR1","doi-asserted-by":"crossref","unstructured":"Avrahami, O., et al.: Stable flow: Vital layers for training-free image editing. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 7877\u20137888 (2025)","DOI":"10.1109\/CVPR52734.2025.00738"},{"key":"6_CR2","unstructured":"Black Forest Labs: Flux (2024). https:\/\/github.com\/black-forest-labs\/flux, Accessed 15 Sep 2025"},{"key":"6_CR3","doi-asserted-by":"crossref","unstructured":"Brooks, T., Holynski, A., Efros, A.A.: Instructpix2pix: Learning to follow image editing instructions. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 18392\u201318402 (2023)","DOI":"10.1109\/CVPR52729.2023.01764"},{"key":"6_CR4","doi-asserted-by":"crossref","unstructured":"Cao, M., Wang, X., Qi, Z., Shan, Y., Qie, X., Zheng, Y.: Masactrl: Tuning-free mutual self-attention control for consistent image synthesis and editing. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 22560\u201322570 (2023)","DOI":"10.1109\/ICCV51070.2023.02062"},{"key":"6_CR5","unstructured":"Deng, Y., He, X., Mei, C., Wang, P., Tang, F.: Fireflow: Fast inversion of rectified flow for image semantic editing. In: Forty-Second International Conference on Machine Learning (2025)"},{"key":"6_CR6","unstructured":"Esser, P., et al.: Scaling rectified flow transformers for high-resolution image synthesis. In: Forty-First International Conference on Machine Learning (2024)"},{"key":"6_CR7","first-page":"6840","volume":"33","author":"J Ho","year":"2020","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. Adv. Neural. Inf. Process. Syst. 33, 6840\u20136851 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"6_CR8","unstructured":"Hu, Y., et al.: Dcedit: Dual-level controlled image editing via precisely localized semantics. arXiv preprint arXiv:2503.16795 (2025)"},{"issue":"13","key":"6_CR9","doi-asserted-by":"publisher","first-page":"800","DOI":"10.1049\/el:20080522","volume":"44","author":"Q Huynh-Thu","year":"2008","unstructured":"Huynh-Thu, Q., Ghanbari, M.: Scope of validity of psnr in image\/video quality assessment. Electron. Lett. 44(13), 800\u2013801 (2008)","journal-title":"Electron. Lett."},{"key":"6_CR10","unstructured":"Jiao, G., Huang, B., Wang, K.C., Liao, R.: Uniedit-flow: Unleashing inversion and editing in the era of flow models. In: The Fourteenth International Conference on Learning Representations (2026)"},{"key":"6_CR11","unstructured":"Ju, X., Zeng, A., Bian, Y., Liu, S., Xu, Q.: Pnp inversion: Boosting diffusion-based editing with 3 lines of code. In: The Twelfth International Conference on Learning Representations (2024)"},{"key":"6_CR12","doi-asserted-by":"crossref","unstructured":"Kirillov, A., et al.: Segment anything. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 4015\u20134026 (2023)","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"6_CR13","doi-asserted-by":"crossref","unstructured":"Kulikov, V., Kleiner, M., Huberman-Spiegelglas, I., Michaeli, T.: Flowedit: Inversion-free text-based editing using pre-trained flow models. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 19721\u201319730 (2025)","DOI":"10.1109\/ICCV51701.2025.01834"},{"key":"6_CR14","unstructured":"Labs, B.F., et\u00a0al.: Flux. 1 kontext: Flow matching for in-context image generation and editing in latent space. arXiv preprint arXiv:2506.15742 (2025)"},{"key":"6_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","volume-title":"Computer Vision \u2013 ECCV 2014","author":"T-Y Lin","year":"2014","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., Zitnick, C.L.: Microsoft COCO: Common Objects in Context. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8693, pp. 740\u2013755. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10602-1_48"},{"key":"6_CR16","unstructured":"Lipman, Y., Chen, R.T.Q., Ben-Hamu, H., Nickel, M., Le, M.: Flow matching for generative modeling. In: The Eleventh International Conference on Learning Representations (2023)"},{"key":"6_CR17","unstructured":"Liu, X., Gong, C., Liu, Q.: Flow straight and fast: Learning to generate and transfer data with rectified flow. In: The Eleventh International Conference on Learning Representations (2023)"},{"key":"6_CR18","unstructured":"Long, Z., et al.: Follow-your-shape: Shape-aware image editing via trajectory-guided region control. In: The Fourteenth International Conference on Learning Representations (2026)"},{"key":"6_CR19","unstructured":"Luo, X., et al.: Editscore: Unlocking online rl for image editing via high-fidelity reward modeling. In: The Fourteenth International Conference on Learning Representations (2026)"},{"key":"6_CR20","doi-asserted-by":"crossref","unstructured":"Ma, Y., Wu, X., Sun, K., Li, H.: Hpsv3: Towards wide-spectrum human preference score. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 15086\u201315095 (2025)","DOI":"10.1109\/ICCV51701.2025.01400"},{"issue":"1","key":"6_CR21","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","volume":"9","author":"N Otsu","year":"1979","unstructured":"Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62\u201366 (1979). https:\/\/doi.org\/10.1109\/TSMC.1979.4310076","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"6_CR22","doi-asserted-by":"crossref","unstructured":"Peebles, W., Xie, S.: Scalable diffusion models with transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4195\u20134205 (2023)","DOI":"10.1109\/ICCV51070.2023.00387"},{"key":"6_CR23","first-page":"606","volume":"5","author":"R Pope","year":"2023","unstructured":"Pope, R., et al.: Efficiently scaling transformer inference. Proc. Mach. Learn. Syst. 5, 606\u2013624 (2023)","journal-title":"Proc. Mach. Learn. Syst."},{"key":"6_CR24","unstructured":"Radford, A., et al.: Learning transferable visual models from natural language supervision. In: International Conference on Machine Learning, pp. 8748\u20138763. PMLR (2021)"},{"key":"6_CR25","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10684\u201310695 (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"6_CR26","unstructured":"Rout, L., Chen, Y., Ruiz, N., Caramanis, C., Shakkottai, S., Chu, W.: Semantic image inversion and editing using rectified stochastic differential equations. In: The Thirteenth International Conference on Learning Representations (2025)"},{"key":"6_CR27","doi-asserted-by":"crossref","unstructured":"Shen, T., et al.: Qk-edit: Revisiting attention-based injection in mm-dit for image and video editing. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 19043\u201319053 (2025)","DOI":"10.1109\/ICCV51701.2025.01770"},{"key":"6_CR28","doi-asserted-by":"crossref","unstructured":"Shin, J., Hwang, A., Kim, Y., Kim, D., Park, J.: Exploring multimodal diffusion transformers for enhanced prompt-based image editing. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 19492\u201319502 (2025)","DOI":"10.1109\/ICCV51701.2025.01812"},{"key":"6_CR29","doi-asserted-by":"crossref","unstructured":"Tumanyan, N., Bar-Tal, O., Bagon, S., Dekel, T.: Splicing vit features for semantic appearance transfer. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10748\u201310757 (2022)","DOI":"10.1109\/CVPR52688.2022.01048"},{"key":"6_CR30","unstructured":"Wang, J., et al.: Taming rectified flow for inversion and editing. In: Forty-second International Conference on Machine Learning (2025)"},{"issue":"4","key":"6_CR31","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"6_CR32","doi-asserted-by":"crossref","unstructured":"Wolsey, L.A.: Integer programming. John Wiley & Sons (2020)","DOI":"10.1002\/9781119606475"},{"key":"6_CR33","unstructured":"Wu, C., et\u00a0al.: Qwen-image technical report. arXiv preprint arXiv:2508.02324 (2025)"},{"key":"6_CR34","unstructured":"Xiao, G., Tian, Y., Chen, B., Han, S., Lewis, M.: Efficient streaming language models with attention sinks. In: The Twelfth International Conference on Learning Representations (2024)"},{"key":"6_CR35","first-page":"124456","volume":"38","author":"C Xie","year":"2026","unstructured":"Xie, C., Li, M., Li, S., Wu, Y., Yi, Q., Zhang, L.: Dnaedit: Direct noise alignment for text-guided rectified flow editing. Adv. Neural. Inf. Process. Syst. 38, 124456\u2013124474 (2026)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"6_CR36","doi-asserted-by":"crossref","unstructured":"Xu, P., et al.: Unveil inversion and invariance in flow transformer for versatile image editing. In: Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 28479\u201328489 (2025)","DOI":"10.1109\/CVPR52734.2025.02652"},{"key":"6_CR37","doi-asserted-by":"crossref","unstructured":"Yang, K., Li, X., Li, Y., Li, Q., Wang, Z.: Fsi-edit: Frequency and stochasticity injection for flexible diffusion-based image editing. In: The Thirty-ninth Annual Conference on Neural Information Processing Systems (2025)","DOI":"10.52202\/085713-4434"},{"key":"6_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 586\u2013595 (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"6_CR39","doi-asserted-by":"crossref","unstructured":"Zhu, T., Zhang, S., Shao, J., Tang, Y.: Kv-edit: Training-free image editing for precise background preservation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 16607\u201316617 (2025)","DOI":"10.1109\/ICCV51701.2025.01542"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2026"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-37167-6_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T08:49:17Z","timestamp":1789116557000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-37167-6_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032371669","9783032371676"],"references-count":39,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-37167-6_6","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"12 September 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Malm\u00f6","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sweden","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 September 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 September 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2026","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}