, Zhiwu Huang, Shuhang Gu and Radu Timofte are the AIM 2020 challenge organizers. http://www.vision.ee.ethz.ch/aim20/ 3 Participants in the challenge. Appendix A contains the authors' teams and affiliations.

Automatic summarization generation of sports video content has been object of great interest for many years. Although semantic descriptions techniques have been proposed, many of the approaches still rely on low-level video descriptors that render quite limited results due to the complexity of the problem and to the low capability of the descriptors to represent semantic content. In this paper, a new approach for automatic highlights summarization generation of soccer videos using audio-visual descriptors is presented. The approach is based on the segmentation of the video sequence into shots that will be further analyzed to determine its relevance and interest. Of special interest in the approach is the use of the audio information that provides additional robustness to the overall performance of the summarization system. For every video shot a set of low and mid level audio-visual descriptors are computed and lately adequately combined in order to obtain different relevance measures based on empirical knowledge rules. The final summary is generated by selecting those shots with highest interest according to the specifications of the user and the results of relevance measures. A variety of results are presented with real soccer video sequences that prove the validity of the approach.

IC Reverse engineering is the process to analyze an integrated circuit to obtain information about its design, materials, logic circuitry, functionality, performance and other relevant features. The increasingly complexity of microchips using a greater number of layers and logic gates makes this process unaffordable when using traditional methods that rely on human inspection and analysis. Therefore, digital image processing is presented as a fruitful field for automation. In this paper a system for the circuitry extraction, analysis and presentation is described. It is divided in three blocks: 2D Image Tiling, Logic Gates Localization & Recognition and Microchip Navigator. The paper presents an overview of the complete system and is mainly based on the description of the image processing algorithms that are applied to the different blocks such as image stitching, customized Scale Invariant Feature Transform (SIFT) and logic gate localization & recognition.Peer ReviewedPostprint (published version

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Automatic generation of sports highlights from recorded audiovisual content has been object of great interest in recent years. The problem is indeed important in the production of second and third division leagues highlights videos where the quantity of raw material is significant and does not contain manual annotations. Many approaches are mostly based on the analysis of the video and disregard the important information provided by the audio track. In this paper, a new approach that combines audio and video descriptors for automatic soccer highlights generation is proposed. The approach is based on the segmentation of the video contents into shots that are further analyzed in order to determine its relevance and interest. These video-shots are scored taking into account the fusion between different audio and video features. The paper is mainly focused to emphasize the importance of audio detectors that play a key role in the analysis and scoring of the video-shots. Specifically, a new algorithm for referee's whistle detection is proposed. The algorithm has been proven to be very robust and efficiently discriminates professional whistles against other types of noises such as public cheering-up, music instruments, etc. Several results have been produced using real soccer video sequences that prove the validity of the proposed audio and video fusion scheme.Peer ReviewedPostprint (published version