Related papers: diveXplore 6.0: ITEC's Interactive Video Explorati…

As a longstanding participating system in the annual Video Browser Showdown (VBS2017-VBS2020) as well as in two iterations of the more recently established Lifelog Search Challenge (LSC2018-LSC2019), diveXplore is developed as a…

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 short overview of search features and some…

According to our experience from VBS2023 and the feedback from the IVR4B special session at CBMI2023, we have largely revised the diveXplore system for VBS2024. It now integrates OpenCLIP trained on the LAION-2B dataset for image/text…

Since its first iteration in 2018, the Lifelog Search Challenge (LSC) - an interactive competition for retrieving lifelogging moments - is co-located at the annual ACM International Conference on Multimedia Retrieval (ICMR) and has drawn…

Since its first iteration in 2018, the Lifelog Search Challenge (LSC) continues to rise in popularity as an interactive lifelog data retrieval competition, co-located at the ACM International Conference on Multimedia Retrieval (ICMR). The…

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 presents an after-the-fact summary of the participation of the vitrivr system to the 2019 Video Browser Showdown. Analogously to last year's report, the focus of this paper lies on additions made since the original publication…

The Video Browser Showdown (VBS) challenges systems to deliver accurate results under strict time constraints. To meet this demand, we present Fusionista2.0, a streamlined video retrieval system optimized for speed and usability. All core…

This paper presents an after-the-fact summary of the participation of the vitrivr system to the 2018 Video Browser Showdown. A particular focus is on additions made since the original publication and the systems performance during the…

In this paper, we describe in details VISIONE, a video search system that allows users to search for videos using textual keywords, occurrence of objects and their spatial relationships, occurrence of colors and their spatial relationships,…

In this report, we present the winning solution that achieved the 1st place in the Complex Video Reasoning & Robustness Evaluation Challenge 2025. This challenge evaluates the ability to generate accurate natural language answers to…

In the era of large language models, Text-to-SQL, as a natural language interface for databases, is playing an increasingly important role. The sota Text-to-SQL models have achieved impressive accuracy, but their performance critically…

Bounded by the inherent ambiguity of depth perception, contemporary camera-based 3D object detection methods fall into the performance bottleneck. Intuitively, leveraging temporal multi-view stereo (MVS) technology is the natural knowledge…

Query-based video situation detection (as opposed to manual or customized algorithms) is critical for diverse applications such as traffic monitoring, surveillance1 , and other types of environmental/infrastructure monitoring. Video…

We introduce DeepSeek-V3.2, a model that harmonizes high computational efficiency with superior reasoning and agent performance. The key technical breakthroughs of DeepSeek-V3.2 are as follows: (1) DeepSeek Sparse Attention (DSA): We…

In recent years, significant developments have been made in both video retrieval and video moment retrieval tasks, which respectively retrieve complete videos or moments for a given text query. These advancements have greatly improved user…

We present the beta release of iDaVIE-v, a new Virtual Reality software for data cube exploration. The beta release of iDaVIE-v (immersive Data Visualisation Interactive Explorer for volumetric rendering) is planned for release in early…

We present an interactive system enabling users to manipulate images to explore the robustness and sensitivity of deep learning image classifiers. Using modern web technologies to run in-browser inference, users can remove image features…

In high-stakes settings, Machine Learning models that can provide predictions that are interpretable for humans are crucial. This is even more true with the advent of complex deep learning based models with a huge number of tunable…

The ACM Lifelog Search Challenge (LSC) is a venue that welcomes and compares systems that support the exploration of lifelog data, and in particular the retrieval of specific information, through an interactive competition format. This…