2020 Proceeding- General Chairs:
- Valerie Gouet-Brunet,
- Margarita Khokhlova,
- Ronak Kosti,
- Liming Chen,
- Xu-Cheng Yin
It is our great pleasure to welcome you to SUMAC 2020, the 2nd edition of the ACM workshop on Structuring and Understanding of Multimedia heritAge Contents. The digitization of large quantities of analogue data and the massive production of born-digital documents for many years now provide us with large volumes of varied multimedia data (images, maps, text, video, multi-sensor data, etc.), an important feature of which is that they are cross-domain. "Cross-domain" reflects the fact that these data may have been acquired in very different conditions: different acquisition systems, times and points of view (e.g. a 1962 postcard from the Arc de Triomphe vs. a recent street-view acquisition by mobile mapping of the same monument). These data represent an extremely rich heritage that can be exploited in a wide variety of fields, from SSH to land use and territorial policies, including smart city, urban planning, tourism, creative media and entertainment.
In terms of research in computer science, they address challenging problems related to the diversity and volume of the media across time, the variety of content descriptors (potentially including the time dimension), the veracity of the data, and the different user needs with respect to engaging with this rich material and the extraction of value out of the data. These challenges are reflected in research topics such as multimodal and mixed media search, automatic content analysis, multimedia linking and recommendation, and big data analysis and visualization, where scientific bottlenecks may be exacerbated by the time dimension, which also provides topics of interest such as multimodal time series analysis.
Proceeding Downloads
Deep Image Features for Instance-level Recognition and Matching
In this talk, I will discuss recent work from our team at Google Research, covering novel methods and datasets. Instance-level recognition, retrieval and matching are key computer vision problems which generally depend on effective image representations,...
Towards the Semantic-aware 3D Digitisation of Architectural Heritage: The "Notre-Dame de Paris" Digital Twin Project
The introduction of digital technologies into the practices of documentation, analysis and dissemination of cultural heritage is today an important issue not only in the sphere of computer science, but also in the humanities and social sciences as well ...
Semantics Preserving Hierarchy based Retrieval of Indian heritage monuments
Monument classification can be performed on the basis of their appearance and shape from coarse to fine categories, although there is much semantic information present in the monuments which is reflected in the eras they were built, its type or purpose, ...
A Generative Adversarial Approach with Residual Learning for Dust and Scratches Artifacts Removal
Retouching can significantly elevate the visual appeal of photos, but many casual photographers lack the expertise to operate in a professional manner. One particularly challenging task for old photo retouching remains the removal of dust and scratches ...
Face Detection on Pre-modern Japanese Artworks using R-CNN and Image Patching for Semi-Automatic Annotation
We propose a face detection method for semi-automatic annotation of faces on pre-modern Japanese artworks to assist art historians identify objects in the art collection. Our method is based on R-CNN, such as Faster R-CNN and Cascade R-CNN, for object ...
An Automated Pipeline for a Browser-based, City-scale Mobile 4D VR Application based on Historical Images
The process for automatically creating 3D city models from contemporary photographs and visualizing them on mobile devices is now well established, but historical 4D city models are more challenging. The fourth dimension here is time. This article ...
New Interactive Methods for Image Registration with Applications in Repeat Photography
We present two methods to interactively register images, which can not be registered automatically due to the large differences between them. Those difference may occur with images which are multitemporal, multisensory, or multipositional. Our methods ...
Hybrid Human-Machine Classification System for Cultural Heritage Data
The advancement of digital technologies has helped cultural heritage organizations to digitize their data collections and improve the accessibility via online platforms. These platforms have enabled citizens to contribute to the process of digital ...
PP-LinkNet: Improving Semantic Segmentation of High Resolution Satellite Imagery with Multi-stage Training
Road network and building footprint extraction is essential for many applications such as updating maps, traffic regulations, city planning, ride-hailing, disaster response etc. Mapping road networks is currently both expensive and labor-intensive. ...
- Proceedings of the 2nd Workshop on Structuring and Understanding of Multimedia heritAge Contents
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Acceptance Rates
| Year | Submitted | Accepted | Rate |
|---|---|---|---|
| SUMAC '22 | 6 | 5 | 83% |
| Overall | 6 | 5 | 83% |