Computer Vision – ECCV 2024 Workshops Milan, Italy, September 29–October 4, 2024, Proceedings, Part XXII /
The multi-volume set LNCS 15623 until LNCS 15646 constitutes the proceedings of the workshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024, which took place in Milan, Italy, during September 29–October 4, 2024. These LNCS volumes contain 574 accepted...
Salvato in:
| Ente Autore: | |
|---|---|
| Altri autori: | , , , |
| Natura: | Elettronico eBook |
| Lingua: | inglese |
| Pubblicazione: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
|
| Edizione: | 1st ed. 2025. |
| Serie: | Lecture Notes in Computer Science,
15644 |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1007/978-3-031-92089-9 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-92089-9 | ||
| 003 | DE-He213 | ||
| 005 | 20260706115951.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 250525s2025 sz | s |||| 0|eng d | ||
| 020 | |a 9783031920899 |9 978-3-031-92089-9 | ||
| 024 | 7 | |a 10.1007/978-3-031-92089-9 |2 doi | |
| 050 | 4 | |a TA1501-1820 | |
| 050 | 4 | |a TA1634 | |
| 072 | 7 | |a UYT |2 bicssc | |
| 072 | 7 | |a COM016000 |2 bisacsh | |
| 072 | 7 | |a UYT |2 thema | |
| 082 | 0 | 4 | |a 006 |2 23 |
| 245 | 1 | 0 | |a Computer Vision – ECCV 2024 Workshops |h [electronic resource] : |b Milan, Italy, September 29–October 4, 2024, Proceedings, Part XXII / |c edited by Alessio Del Bue, Cristian Canton, Jordi Pont-Tuset, Tatiana Tommasi. |
| 250 | |a 1st ed. 2025. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2025. | |
| 300 | |a LV, 408 p. 146 illus., 141 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
| 341 | 0 | |b Use of color is not sole means of conveying information |2 onix | |
| 341 | 0 | |b Use of high contrast between text and background color |2 onix | |
| 341 | 0 | |b Next / Previous structural navigation |2 onix | |
| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Lecture Notes in Computer Science, |x 1611-3349 ; |v 15644 | |
| 505 | 0 | |a -- Landmark-Based Screening: Femoral Head Coverage and Graf Classification in Infant Developmental Dysplasia of the Hip. -- MVTN: A Multiscale Video Transformer Network for Hand Gesture Recognition. -- One-Shot Image Restoration. -- Medical Image Segmentation with SAM-generated Annotations. -- Manipulating and Mitigating Generative Model Biases without Retraining. -- Fake or JPEG? Revealing Common Biases in Generated Image Detection Datasets. -- Generated Bias: Auditing Internal Bias Dynamics of Text-To-Image Generative Models. -- A semiotic methodology for assessing the compositional effectiveness of generative text-to-image models (Midjourney and DALLoE). -- A Framework for Critical Evaluation of Text-to-Image Models: Integrating Art Historical Analysis, Artistic Exploration, and Critical Prompt Engineering. -- Civiverse: A Dataset for Analyzing User Engagement with Open-Source TTI-Models. -- Exploring the Boundaries of Content Moderation in Text-to-Image Generation. -- Rethinking HTG Evaluation: Bridging Generation and Recognition. -- Evaluation Framework for Feedback Generation Methods in Skeletal Movement Assessment. -- FaceOracle: Chat with a Face Image Oracle. -- Makeup-Guided Facial Privacy Protection via Untrained Neural Network Priors. -- How to Squeeze An Explanation Out of Your Model. -- How were you created? Explaining synthetic face images generated by diffusion models. -- Frequency Matters: Explaining Biases of Face Recognition in the Frequency Domain. -- How green is continual learning, really? Analyzing the energy consumption in continual training of vision foundation models. -- Architecture-Agnostic Unsupervised Gradient Regularization For Parameter-Efficient Transfer Learning. -- Foundation Model or Finetune? Evaluation of few-shot semantic segmentation for river pollution. -- Personalizing Multimodal Large Language Models for Image Captioning: An Experimental Analysis. -- Improved Baselines for Data-efficient Perceptual Augmentation of LLMs. -- Watt for What: Rethinking Deep Learning’s Energy-Performance Relationship. | |
| 520 | |a The multi-volume set LNCS 15623 until LNCS 15646 constitutes the proceedings of the workshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024, which took place in Milan, Italy, during September 29–October 4, 2024. These LNCS volumes contain 574 accepted papers from 53 of the 73 workshops. The list of workshops and distribution of the workshop papers in the LNCS volumes can be found in the preface that is freely accessible online. . | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 650 | 0 | |a Image processing |x Digital techniques. | |
| 650 | 0 | |a Computer vision. | |
| 650 | 0 | |a Image processing. | |
| 650 | 0 | |a User interfaces (Computer systems). | |
| 650 | 0 | |a Human-computer interaction. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Computers, Special purpose. | |
| 650 | 1 | 4 | |a Computer Imaging, Vision, Pattern Recognition and Graphics. |
| 650 | 2 | 4 | |a Image Processing. |
| 650 | 2 | 4 | |a User Interfaces and Human Computer Interaction. |
| 650 | 2 | 4 | |a Machine Learning. |
| 650 | 2 | 4 | |a Special Purpose and Application-Based Systems. |
| 700 | 1 | |a Del Bue, Alessio. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Canton, Cristian. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Pont-Tuset, Jordi. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 700 | 1 | |a Tommasi, Tatiana. |e editor. |4 edt |4 http://id.loc.gov/vocabulary/relators/edt | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031920882 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031920905 |
| 830 | 0 | |a Lecture Notes in Computer Science, |x 1611-3349 ; |v 15644 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-92089-9 |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 912 | |a ZDB-2-SXPS | ||
| 912 | |a ZDB-2-LNC | ||
| 912 | |a ZDB-2-241 | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||
| 950 | |a Springer Nature Proceedings Computer Science (SpringerNature-85344) | ||
| 950 | |a Focus Bundle Computer Vision and Pattern Recognition (SpringerNature-85411) | ||