5 citations · 13 across the 6 of their papers we have counts for
6 papers
Fast Hierarchical Learning for Few-Shot Object Detection
Yihang She, Goutam Bhat, Martin Danelljan +1
Transfer learning based approaches have recently achieved promising results on the few-shot detection task. These approaches however suffer from ``catastrophic forgetting'' issue d…
Arbitrary-Scale Image Synthesis
Evangelos Ntavelis, Mohamad Shahbazi, Iason Kastanis +3
Positional encodings have enabled recent works to train a single adversarial network that can generate images of different scales. However, these approaches are either limited to a…
Transforming Model Prediction for Tracking
Christoph Mayer, Martin Danelljan, Goutam Bhat +4
Optimization based tracking methods have been widely successful by integrating a target model prediction module, providing effective global reasoning by minimizing an objective fun…
Adiabatic Quantum Computing for Multi Object Tracking
Jan-Nico Zaech, Alexander Liniger, Martin Danelljan +2
Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection paradigm, where object detections are associated through time. The association step naturally lead…
Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution
Andreas Lugmayr, Martin Danelljan, Fisher Yu +2
Super-resolution is an ill-posed problem, where a ground-truth high-resolution image represents only one possibility in the space of plausible solutions. Yet, the dominant paradigm…
PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
Prune Truong, Martin Danelljan, Radu Timofte +1
Establishing robust and accurate correspondences between a pair of images is a long-standing computer vision problem with numerous applications. While classically dominated by spar…