60 citations · 76 across the 7 of their papers we have counts for
19 papers
DESC: Domain Adaptation for Depth Estimation via Semantic Consistency
Adrian Lopez-Rodriguez, Krystian Mikolajczyk
Accurate real depth annotations are difficult to acquire, needing the use of special devices such as a LiDAR sensor. Self-supervised methods try to overcome this problem by process…
Cascaded channel pruning using hierarchical self-distillation
Roy Miles, Krystian Mikolajczyk
In this paper, we propose an approach for filter-level pruning with hierarchical knowledge distillation based on the teacher, teaching-assistant, and student framework. Our method…
Project to Adapt: Domain Adaptation for Depth Completion from Noisy and Sparse Sensor Data
Adrian Lopez-Rodriguez, Benjamin Busam, Krystian Mikolajczyk
Depth completion aims to predict a dense depth map from a sparse depth input. The acquisition of dense ground truth annotations for depth completion settings can be difficult and,…
HyNet: Learning Local Descriptor with Hybrid Similarity Measure and Triplet Loss
Yurun Tian, Axel Barroso-Laguna, Tony Ng +2
Recent works show that local descriptor learning benefits from the use of L2 normalisation, however, an in-depth analysis of this effect lacks in the literature. In this paper, we…
D2D: Keypoint Extraction with Describe to Detect Approach
Yurun Tian, Vassileios Balntas, Tony Ng +3
In this paper, we present a novel approach that exploits the information within the descriptor space to propose keypoint locations. Detect then describe, or detect and describe joi…
HDD-Net: Hybrid Detector Descriptor with Mutual Interactive Learning
Axel Barroso-Laguna, Yannick Verdie, Benjamin Busam +1
Local feature extraction remains an active research area due to the advances in fields such as SLAM, 3D reconstructions, or AR applications. The success in these applications relie…