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Make One-Shot Video Object Segmentation Efficient Again
Tim Meinhardt, Laura Leal-Taixe
Video object segmentation (VOS) describes the task of segmenting a set of objects in each frame of a video. In the semi-supervised setting, the first mask of each object is provide…
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences
Qunjie Zhou, Torsten Sattler, Laura Leal-Taixe
The classical matching pipeline used for visual localization typically involves three steps: (i) local feature detection and description, (ii) feature matching, and (iii) outlier r…
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…
Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation
Patrick Dendorfer, Aljoša Ošep, Laura Leal-Taixé
In this paper, we present Goal-GAN, an interpretable and end-to-end trainable model for human trajectory prediction. Inspired by human navigation, we model the task of trajectory p…
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…
HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking
Jonathon Luiten, Aljosa Osep, Patrick Dendorfer +4
Multi-Object Tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association. To address this, we presen…
Making a Case for 3D Convolutions for Object Segmentation in Videos
Sabarinath Mahadevan, Ali Athar, Aljoša Ošep +3
The task of object segmentation in videos is usually accomplished by processing appearance and motion information separately using standard 2D convolutional networks, followed by a…
Planning from Images with Deep Latent Gaussian Process Dynamics
Nathanael Bosch, Jan Achterhold, Laura Leal-Taixé +1
Planning is a powerful approach to control problems with known environment dynamics. In unknown environments the agent needs to learn a model of the system dynamics to make plannin…
HOLISMOKES -- II. Identifying galaxy-scale strong gravitational lenses in Pan-STARRS using convolutional neural networks
R. Canameras, S. Schuldt, S. H. Suyu +6
We present a systematic search for wide-separation (Einstein radius >1.5"), galaxy-scale strong lenses in the 30 000 sq.deg of the Pan-STARRS 3pi survey on the Northern sky. With l…
STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos
Ali Athar, Sabarinath Mahadevan, Aljoša Ošep +2
Existing methods for instance segmentation in videos typically involve multi-stage pipelines that follow the tracking-by-detection paradigm and model a video clip as a sequence of…
Lake Ice Monitoring with Webcams and Crowd-Sourced Images
Rajanie Prabha, Manu Tom, Mathias Rothermel +3
Lake ice is a strong climate indicator and has been recognised as part of the Essential Climate Variables (ECV) by the Global Climate Observing System (GCOS). The dynamics of freez…