118 citations · 258 across the 21 of their papers we have counts for
7 papers · 1 filter
EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes
Hoang-An Le, Thomas Mensink, Partha Das +2
Multimodal large-scale datasets for outdoor scenes are mostly designed for urban driving problems. The scenes are highly structured and semantically different from scenarios seen i…
Novel View Synthesis from Single Images via Point Cloud Transformation
Hoang-An Le, Thomas Mensink, Partha Das +1
In this paper the argument is made that for true novel view synthesis of objects, where the object can be synthesized from any viewpoint, an explicit 3D shape representation isdesi…
Multi-Loss Weighting with Coefficient of Variations
Rick Groenendijk, Sezer Karaoglu, Theo Gevers +1
Many interesting tasks in machine learning and computer vision are learned by optimising an objective function defined as a weighted linear combination of multiple losses. The fina…
PointMixup: Augmentation for Point Clouds
Yunlu Chen, Vincent Tao Hu, Efstratios Gavves +4
This paper introduces data augmentation for point clouds by interpolation between examples. Data augmentation by interpolation has shown to be a simple and effective approach in th…
Post-hoc Calibration of Neural Networks by g-Layers
Amir Rahimi, Thomas Mensink, Kartik Gupta +3
Calibration of neural networks is a critical aspect to consider when incorporating machine learning models in real-world decision-making systems where the confidence of decisions a…
Calibration of Neural Networks using Splines
Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan +3
Calibrating neural networks is of utmost importance when employing them in safety-critical applications where the downstream decision making depends on the predicted probabilities.…
Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection
Alex Bewley, Pei Sun, Thomas Mensink +2
This paper presents a novel 3D object detection framework that processes LiDAR data directly on its native representation: range images. Benefiting from the compactness of range im…