activity
20152026
most citedMOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking

650 citations · 1.6k across the 46 of their papers we have counts for

collaborators
Showing 2020 · cs.CVShow all

17 papers · 2 filters

cs.CV2020

Crop Classification under Varying Cloud Cover with Neural Ordinary Differential Equations

Nando Metzger, Mehmet Ozgur Turkoglu, Stefano D'Aronco +2

Optical satellite sensors cannot see the Earth's surface through clouds. Despite the periodic revisit cycle, image sequences acquired by Earth observation satellites are therefore…

cs.CV2020

PREDATOR: Registration of 3D Point Clouds with Low Overlap

Shengyu Huang, Zan Gojcic, Mikhail Usvyatsov +2

We introduce PREDATOR, a model for pairwise point-cloud registration with deep attention to the overlap region. Different from previous work, our model is specifically designed to…

cs.CV2020

Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams using Machine Learning

Manu Tom, Rajanie Prabha, Tianyu Wu +3

Continuous observation of climate indicators, such as trends in lake freezing, is important to understand the dynamics of the local and global climate system. Consequently, lake ic…

cs.CV2020

MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking

Patrick Dendorfer, Aljoša Ošep, Anton Milan +5

Standardized benchmarks have been crucial in pushing the performance of computer vision algorithms, especially since the advent of deep learning. Although leaderboards should not b…

cs.CV2020★ 20 cited

Deep Active Learning in Remote Sensing for data efficient Change Detection

Vít Růžička, Stefano D'Aronco, Jan Dirk Wegner +1

We investigate active learning in the context of deep neural network models for change detection and map updating. Active learning is a natural choice for a number of remote sensin…

cs.CV2020

KAPLAN: A 3D Point Descriptor for Shape Completion

Audrey Richard, Ian Cherabier, Martin R. Oswald +2

We present a novel 3D shape completion method that operates directly on unstructured point clouds, thus avoiding resource-intensive data structures like voxel grids. To this end, w…