206 citations · 337 across the 15 of their papers we have counts for
20 papers
Continual Domain Adaptation on Aerial Images under Gradually Degrading Weather
Chowdhury Sadman Jahan, Andreas Savakis
Domain adaptation (DA) strives to mitigate the domain gap between the source domain where a model is trained, and the target domain where the model is deployed. When a deep learnin…
Curriculum Guided Domain Adaptation in the Dark
Chowdhury Sadman Jahan, Andreas Savakis
Addressing the rising concerns of privacy and security, domain adaptation in the dark aims to adapt a black-box source trained model to an unlabeled target domain without access to…
DeepRM: Deep Recurrent Matching for 6D Pose Refinement
Alexander Avery, Andreas Savakis
Precise 6D pose estimation of rigid objects from RGB images is a critical but challenging task in robotics, augmented reality and human-computer interaction. To address this proble…
BAPose: Bottom-Up Pose Estimation with Disentangled Waterfall Representations
Bruno Artacho, Andreas Savakis
We propose BAPose, a novel bottom-up approach that achieves state-of-the-art results for multi-person pose estimation. Our end-to-end trainable framework leverages a disentangled m…
Extreme Face Inpainting with Sketch-Guided Conditional GAN
Nilesh Pandey, Andreas Savakis
Recovering badly damaged face images is a useful yet challenging task, especially in extreme cases where the masked or damaged region is very large. One of the major challenges is…
Grassmann Iterative Linear Discriminant Analysis with Proxy Matrix Optimization
Navya Nagananda, Breton Minnehan, Andreas Savakis
Linear Discriminant Analysis (LDA) is commonly used for dimensionality reduction in pattern recognition and statistics. It is a supervised method that aims to find the most discrim…