206 citations · 337 across the 15 of their papers we have counts for
19 papers · 1 filter
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…
SiamReID: Confuser Aware Siamese Tracker with Re-identification Feature
Abu Md Niamul Taufique, Andreas Savakis, Michael Braun +4
Siamese deep-network trackers have received significant attention in recent years due to their real-time speed and state-of-the-art performance. However, Siamese trackers suffer fr…
ConDA: Continual Unsupervised Domain Adaptation
Abu Md Niamul Taufique, Chowdhury Sadman Jahan, Andreas Savakis
Domain Adaptation (DA) techniques are important for overcoming the domain shift between the source domain used for training and the target domain where testing takes place. However…
Benchmarking Deep Trackers on Aerial Videos
Abu Md Niamul Taufique, Breton Minnehan, Andreas Savakis
In recent years, deep learning-based visual object trackers have achieved state-of-the-art performance on several visual object tracking benchmarks. However, most tracking benchmar…
Visualization of Deep Transfer Learning In SAR Imagery
Abu Md Niamul Taufique, Navya Nagananda, Andreas Savakis
Synthetic Aperture Radar (SAR) imagery has diverse applications in land and marine surveillance. Unlike electro-optical (EO) systems, these systems are not affected by weather cond…
Automatic Quantification of Facial Asymmetry using Facial Landmarks
Abu Md Niamul Taufique, Andreas Savakis, Jonathan Leckenby
One-sided facial paralysis causes uneven movements of facial muscles on the sides of the face. Physicians currently assess facial asymmetry in a subjective manner based on their cl…
OmniPose: A Multi-Scale Framework for Multi-Person Pose Estimation
Bruno Artacho, Andreas Savakis
We propose OmniPose, a single-pass, end-to-end trainable framework, that achieves state-of-the-art results for multi-person pose estimation. Using a novel waterfall module, the Omn…
LABNet: Local Graph Aggregation Network with Class Balanced Loss for Vehicle Re-Identification
Abu Md Niamul Taufique, Andreas Savakis
Vehicle re-identification is an important computer vision task where the objective is to identify a specific vehicle among a set of vehicles seen at various viewpoints. Recent meth…
UniPose: Unified Human Pose Estimation in Single Images and Videos
Bruno Artacho, Andreas Savakis
We propose UniPose, a unified framework for human pose estimation, based on our "Waterfall" Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose…
Waterfall Atrous Spatial Pooling Architecture for Efficient Semantic Segmentation
Bruno Artacho, Andreas Savakis
We propose a new efficient architecture for semantic segmentation, based on a "Waterfall" Atrous Spatial Pooling architecture, that achieves a considerable accuracy increase while…
Poly-GAN: Multi-Conditioned GAN for Fashion Synthesis
Nilesh Pandey, Andreas Savakis
We present Poly-GAN, a novel conditional GAN architecture that is motivated by Fashion Synthesis, an application where garments are automatically placed on images of human models a…
Cascaded Projection: End-to-End Network Compression and Acceleration
Breton Minnehan, Andreas Savakis
We propose a data-driven approach for deep convolutional neural network compression that achieves high accuracy with high throughput and low memory requirements. Current network co…
DEFRAG: Deep Euclidean Feature Representations through Adaptation on the Grassmann Manifold
Breton Minnehan, Andreas Savakis
We propose a novel technique for training deep networks with the objective of obtaining feature representations that exist in a Euclidean space and exhibit strong clustering behavi…
Anomaly Detection in Video Using Predictive Convolutional Long Short-Term Memory Networks
Jefferson Ryan Medel, Andreas Savakis
Automating the detection of anomalous events within long video sequences is challenging due to the ambiguity of how such events are defined. We approach the problem by learning gen…