5 papers · 1 filter
X-MULTI: VLM-based Imaging Factor Disentanglement for Factor-Aware Image Synthesis
Sonali Godavarthy, Matthias Neuwirth-Trapp, Tim-Felix Faasch +4
Imaging factor disentanglement in text-to-image generation aims to independently control image acquisition properties such as types of camera lenses, sensor types, viewpoints, and…
MIVIFI: Bridging Perspective and Fisheye Domains for Training Multi-View Fisheye Image Generation Models
Matthias Neuwirth-Trapp, Begüm Altunbas, Jiayi Wang +4
Achieving 360° coverage is critical for the visual perception systems of autonomous vehicles. Fisheye cameras offer a cost-effective solution by enabling full surround coverage wit…
MULTI: Disentangling Camera Lens, Sensor, View, and Domain for Novel Image Generation
Sonali Godavarthy, Matthias Neuwirth-Trapp, Tim-Felix Faasch +3
Recent text-to-image models produce high-quality images, yet text ambiguity hinders precise control when specific styles or objects are required. There have been a number of recent…
Incremental Object Detection with Prompt-based Methods
Matthias Neuwirth-Trapp, Maarten Bieshaar, Danda Pani Paudel +1
Visual prompt-based methods have seen growing interest in incremental learning (IL) for image classification. These approaches learn additional embedding vectors while keeping the…
RICO: Two Realistic Benchmarks and an In-Depth Analysis for Incremental Learning in Object Detection
Matthias Neuwirth-Trapp, Maarten Bieshaar, Danda Pani Paudel +1
Incremental Learning (IL) trains models sequentially on new data without full retraining, offering privacy, efficiency, and scalability. IL must balance adaptability to new data wi…