Recent News

Winner of the SISAP Indexing Challange

Our adaption of the Exploration Graph to low recall regimes won us the SISAP Indexing Challange.

PicArrange 3.0 now finds images with words

Find your photos with words

PicArrange 3.0 allows to find your images with descriptions. Similarity search has been improved.

Creating sorted grid layouts with gradient-based optimization

Gradient-based sorting of 2D grid layouts

At ICMR’24 we presented the first paper on gradient-based sorting of grid layouts.

Continuous Refining Exploration Graph for Multimedia Retrieval

Exploration Graph for Multimedia Retrieval

At ICMR’24 we presented our work on efficient multimedia retrieval using a continuous refining Exploration Graph.

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About Us Visual Computing Group @ HTW Berlin

About Us

The Visual Computing Group is a collaboration of various researchers at the HTW Berlin who work in the fields of:

  • Machine Learning
  • Information Retrieval
  • Visual clustering & sorting
  • Computer Vision
  • Immersive Imaging
  • Neural Rendering
More about us

Awards

SISAP Indexing Challenge 2024
We participated in the SISAP Indexing Challenge for the first time, competing in Tracks 1 and 3, and won both.
LSC Runner-up / Best New Entrant Award
We achieved the Runner-up position and won the Best New Entrant Award at the Life Search Challenge 2024, competing against 21 teams.
Best Textual KIS/Experts
Winner of the 2024 VBS Textual Known Item Search challenge
VBS 2023 Overall Winner
Consecutive Winner of the 2023 Video Browser Showdown
See all our awards

Recent Publications

Adapting the Exploration Graph for High Throughput in Low Recall Regimes

Adapting the Exploration Graph for High Throughput in Low Recall Regimes

Nico Hezel, Bruno Schilling, Kai Uwe Barthel, Konstantin Schall, Klaus Jung
17th International Conference on Similarity Search and Applications (SISAP 2024)

We adapted our Exploration Graph for low-recall regimes and large-scale datasets (≥100 million data points) by integrating feature compression, path optimization, and smart entry points. These enhancements led to our success in the SISAP Indexing Challenge.

Creating Sorted Grid Layouts with Gradient-based Optimization

Creating Sorted Grid Layouts with Gradient-based Optimization

Kai Uwe Barthel, Florian Tim Barthel, Peter Eisert, Nico Hezel, Konstantin Schall
2024 International Conference on Multimedia Retrieval (ICMR '24)

This paper introduces a gradient-based optimization method for efficiently arranging high-dimensional vectors on 2D grids, using a novel loss function to balance valid permutations and similarity-based arrangement for improved sorting quality.

Libro - Lifelog Search Browser

Libro - Lifelog Search Browser

Nico Hezel, Konstantin Schall, Bruno Schilling, Klaus Jung, Kai Uwe Barthel
7th Annual ACM Workshop on the Lifelog Search Challenge (LSC '24)

This paper introduces Libro, a powerful tool for interactive image retrieval and browsing, which won the Runner-up and the Best New Entrant awards at the Lifelog Search Challenge 2024.

An Exploration Graph with Continuous Refinement for Efficient Multimedia Retrieval

An Exploration Graph with Continuous Refinement for Efficient Multimedia Retrieval

Nico Hezel, Kai Uwe Barthel, Konstantin Schall, Klaus Jung
2024 International Conference on Multimedia Retrieval (ICMR '24)

As datasets get larger, searching within them becomes slower. This paper presents a continuous refining Exploration Graph (crEG) for Approximate Nearest Neighbor Search in large multimedia databases. The new graph provides a best balance between search speed and accuracy.

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