Recent News

US Patent Granted

Our US patent "Real Time Spherical Light Field Reconstruction from a Single Omnidirectional Image", US 12,705,687 B2, was granted on August 11, 2026.

Outstanding Editorial Board Member Award 2024

Sebastian Knorr was awarded the Outstanding Editorial Board Member Award 2024 from the IEEE Signal Processing Society for his service for the IEEE Transactions on Image Processing.

PicArrange now finds images with colors

New: PicArrange 3.4 Find Images by Text, Image, and Now, Color

🎨 Find images with similar colors
📍 Search photos by location
🧭 Filter images using GPS data

Tutorial on Visual Information Retrieval

The slides and Jupyter notebooks of our ECIR2025 tutorial are available.

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

Recent Publications

Real-time position-aware view synthesis from single-view input

Manu Gond, Emin Zerman, Sebastian Knorr, and Mårten Sjöström
Signal Processing: Image Communication 2026

We present a lightweight, position-aware network designed for real-time view synthesis from a single input image and a target camera pose.

A STUDY OF RESOLUTION-AWARE VIDEO COMPRESSION FOR REMOTE PHOTOPLETHYSMOGRAPHY

Ruben Hermann Felix Saitz, Jonas Quinque, Burkart Voß, Johannes Franz Trabert, and Sebastian Knorr
IEEE International Conference on Image Processing (ICIP 2026)

This paper investigates how codec choice, constant-quantisation parameter (QP) settings, and spatial resolution jointly affect rPPG accuracy.

The Impact of Intrinsic Scene Cues on Perceived Color Transfer Quality

Herbert Potechius, Thomas Sikora, Sebastian Knorr
IEEE International Conference on Image Processing (ICIP 2026)

In this paper, we investigate the influence of intrinsic scene cues, namely semantics, illumination, and geometry, on the perceived quality of color transfer results.

PVSDNet: Joint Depth Prediction and View Synthesis Via Shared Latent Spaces in Real-Time

Manu Gond, Emin Zerman, Sebastian Knorr, and Mårten Sjöström
IEEE Access 2026

We propose an unified multimodal network capable of jointly synthesizing new views and predicting consistent depth maps from a single input image.

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