107 citations · 131 across the 44 of their papers we have counts for
21 papers · 1 filter
Distill the Best, Ignore the Rest: Improving Dataset Distillation with Loss-Value-Based Pruning
Brian B. Moser, Federico Raue, Tobias C. Nauen +2
Dataset distillation has gained significant interest in recent years, yet existing approaches typically distill from the entire dataset, potentially including non-beneficial sample…
Zoomed In, Diffused Out: Towards Local Degradation-Aware Multi-Diffusion for Extreme Image Super-Resolution
Brian B. Moser, Stanislav Frolov, Tobias C. Nauen +2
Large-scale, pre-trained Text-to-Image (T2I) diffusion models have gained significant popularity in image generation tasks and have shown unexpected potential in image Super-Resolu…
TKG-DM: Training-free Chroma Key Content Generation Diffusion Model
Ryugo Morita, Stanislav Frolov, Brian Bernhard Moser +4
Diffusion models have enabled the generation of high-quality images with a strong focus on realism and textual fidelity. Yet, large-scale text-to-image models, such as Stable Diffu…
Just Leaf It: Accelerating Diffusion Classifiers with Hierarchical Class Pruning
Arundhati S. Shanbhag, Brian B. Moser, Tobias C. Nauen +3
Diffusion models, celebrated for their generative capabilities, have recently demonstrated surprising effectiveness in image classification tasks by using Bayes' theorem. Yet, curr…
A Low-Resolution Image is Worth 1x1 Words: Enabling Fine Image Super-Resolution with Transformers and TaylorShift
Sanath Budakegowdanadoddi Nagaraju, Brian Bernhard Moser, Tobias Christian Nauen +3
Transformer-based architectures have recently advanced the image reconstruction quality of super-resolution (SR) models. Yet, their scalability remains limited by quadratic attenti…
FedAD-Bench: A Unified Benchmark for Federated Unsupervised Anomaly Detection in Tabular Data
Ahmed Anwar, Brian Moser, Dayananda Herurkar +4
The emergence of federated learning (FL) presents a promising approach to leverage decentralized data while preserving privacy. Furthermore, the combination of FL and anomaly detec…
Webcam-based Pupil Diameter Prediction Benefits from Upscaling
Vijul Shah, Brian B. Moser, Ko Watanabe +1
Capturing pupil diameter is essential for assessing psychological and physiological states such as stress levels and cognitive load. However, the low resolution of images in eye da…
SpotDiffusion: A Fast Approach For Seamless Panorama Generation Over Time
Stanislav Frolov, Brian B. Moser, Andreas Dengel
Generating high-resolution images with generative models has recently been made widely accessible by leveraging diffusion models pre-trained on large-scale datasets. Various techni…
PupilSense: A Novel Application for Webcam-Based Pupil Diameter Estimation
Vijul Shah, Ko Watanabe, Brian B. Moser +1
Measuring pupil diameter is vital for gaining insights into physiological and psychological states - traditionally captured by expensive, specialized equipment like Tobii eye-track…
oTTC: Object Time-to-Contact for Motion Estimation in Autonomous Driving
Abdul Hannan Khan, Syed Tahseen Raza Rizvi, Dheeraj Varma Chittari Macharavtu +1
Autonomous driving systems require a quick and robust perception of the nearby environment to carry out their routines effectively. With the aim to avoid collisions and drive safel…
Federated Learning for Blind Image Super-Resolution
Brian B. Moser, Ahmed Anwar, Federico Raue +2
Traditional blind image SR methods need to model real-world degradations precisely. Consequently, current research struggles with this dilemma by assuming idealized degradations, w…
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data
Dayananda Herurkar, Sebastian Palacio, Ahmed Anwar +2
Anomaly detection in real-world scenarios poses challenges due to dynamic and often unknown anomaly distributions, requiring robust methods that operate under an open-world assumpt…
Data Collection of Real-Life Knowledge Work in Context: The RLKWiC Dataset
Mahta Bakhshizadeh, Christian Jilek, Markus Schröder +2
Over the years, various approaches have been employed to enhance the productivity of knowledge workers, from addressing psychological well-being to the development of personal know…
ObjBlur: A Curriculum Learning Approach With Progressive Object-Level Blurring for Improved Layout-to-Image Generation
Stanislav Frolov, Brian B. Moser, Sebastian Palacio +1
We present ObjBlur, a novel curriculum learning approach to improve layout-to-image generation models, where the task is to produce realistic images from layouts composed of boxes…
CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for Named Entity Recognition and Relation Extraction
Neda Foroutan, Markus Schröder, Andreas Dengel
The process of cyber mapping gives insights in relationships among financial entities and service providers. Centered around the outsourcing practices of companies within fund pros…
A Study in Dataset Pruning for Image Super-Resolution
Brian B. Moser, Federico Raue, Andreas Dengel
In image Super-Resolution (SR), relying on large datasets for training is a double-edged sword. While offering rich training material, they also demand substantial computational an…
Unlocking Dataset Distillation with Diffusion Models
Brian B. Moser, Federico Raue, Sebastian Palacio +2
Dataset distillation seeks to condense datasets into smaller but highly representative synthetic samples. While diffusion models now lead all generative benchmarks, current distill…
TaylorShift: Shifting the Complexity of Self-Attention from Squared to Linear (and Back) using Taylor-Softmax
Tobias Christian Nauen, Sebastian Palacio, Andreas Dengel
The quadratic complexity of the attention mechanism represents one of the biggest hurdles for processing long sequences using Transformers. Current methods, relying on sparse repre…
Real-time Traffic Object Detection for Autonomous Driving
Abdul Hannan Khan, Syed Tahseen Raza Rizvi, Andreas Dengel
With recent advances in computer vision, it appears that autonomous driving will be part of modern society sooner rather than later. However, there are still a significant number o…
Modular Graph Extraction for Handwritten Circuit Diagram Images
Johannes Bayer, Leo van Waveren, Andreas Dengel
As digitization in engineering progressed, circuit diagrams (also referred to as schematics) are typically developed and maintained in computer-aided engineering (CAE) systems, thu…
Diffusion Models, Image Super-Resolution And Everything: A Survey
Brian B. Moser, Arundhati S. Shanbhag, Federico Raue +3
Diffusion Models (DMs) have disrupted the image Super-Resolution (SR) field and further closed the gap between image quality and human perceptual preferences. They are easy to trai…