With the widespread use of smartphones as recording devices and the massive growth in bandwidth, the number and volume of video collections has increased significantly in the last years. This poses no...

With the recent resurgence of neural networks and the proliferation of massive amounts of unlabeled multimodal data, recommendation systems and multimodal retrieval systems based on continuous represe...

With our submission to the 2017 TRECVID Instance Search task (Awad et al., 2017b), we focused on the usage of dedicated CNN models. We limited the available video training data to only three sources: ...

Web image analysis has witnessed an AI renaissance. The ILSVRC benchmark has been instrumental in providing a corpus and standardized evaluation. The NVIDIA AI City Challenge is envisioned to provide ...

We report on our system used in the TRECVID 2017 Multimedia Event Detection (MED) and Ad-hoc Video Search (AVS) tasks. On the MED task, the CMU team submitted runs in 010Ex settings for the Pre-specif...

We present a tutorial focusing on video retrieval tasks, where state-of-the-art deep learning approaches still benefit from interactive decisions of users. The tutorial covers general introduction to ...

We present a modern interactive video retrieval tool, called diveXplore, that has been used for several iterations of the Video Browser Showdown (VBS) competition with great success – 2nd place for th...

We present Direct Assessment, a method for manually assessing the quality of automatically-generated captions for video. Evaluating the accuracy of video captions is particularly difficult because for...

We participated in the matching and ranking subtask in TRECVid challenge 2017. The task here was to return a ranked list of the most likely text descriptions that correspond to each video. We adopted ...

We describe our approaches that were tested in the TRECVID 2017 Instance Search (INS) task. In this year’s INS, shots including a person at a location were to be retrieved after a location query and p...

Video hyperlinking is a task aiming to enhance the accessibility of large archives, by establishing links between fragments of videos. The links model the aboutness between fragments for efficient tra...

Video description is the automatic generation of natural language sentences that describe the contents of a given video. It has applications in human-robot interaction, helping the visually impaired a...

Video content has been increasing at an unprecedented rate in recent years, bringing the need for improved tools providing efficient access to specific contents of interest. Within the management of v...

This work summarizes the findings of the 7th iteration of the Video Browser Showdown (VBS) competition organized as a workshop at the 24th International Conference on Multimedia Modeling in Bangkok. T...

This short paper provides further details of the diveXplore system (formerly known as CoViSS), which has been used by team ITEC1 for the Video Browser Showdown (VBS) 2018. In particular, it gives a sh...

This short paper provides further details of the Sloth Search System, which was developed by the NECTEC team for the Video Browser Showdown (VBS) 2018.

This paper provides an overview of the runs submitted to TRECVID 2018 by ITI-CERTH. ITI-CERTH participated in the Ad-hoc Video Search (AVS), Instance Search (INS) and Activities in Extended Video (Act...

This paper proposes a fundamental answer to a frequently asked question in multimedia computing and machine learning: Do artifacts from perceptual compression contribute to error in the machine learni...

This paper presents the runs that were submitted to the TRECVid Challenge 2017 for the Video Hyperlinking task. The goal of the task is to propose a list of video segments, called targets, to compleme...

This paper presents the result of the TRECVID 2017 AVS task by kobe nict siegen team. Consisting of three research institutes Kobe University, NICT and University of Siegen. We submitted the following...