17 citations · 24 across the 5 of their papers we have counts for
13 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…
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…
Deep Reparametrization of Multi-Frame Super-Resolution and Denoising
Goutam Bhat, Martin Danelljan, Fisher Yu +2
We propose a deep reparametrization of the maximum a posteriori formulation commonly employed in multi-frame image restoration tasks. Our approach is derived by introducing a learn…
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results
Goutam Bhat, Martin Danelljan, Radu Timofte +25
This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times hig…
Generating Masks from Boxes by Mining Spatio-Temporal Consistencies in Videos
Bin Zhao, Goutam Bhat, Martin Danelljan +2
Segmenting objects in videos is a fundamental computer vision task. The current deep learning based paradigm offers a powerful, but data-hungry solution. However, current datasets…
Deep Burst Super-Resolution
Goutam Bhat, Martin Danelljan, Luc Van Gool +1
While single-image super-resolution (SISR) has attracted substantial interest in recent years, the proposed approaches are limited to learning image priors in order to add high fre…