DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation

no code implementations • CVPR 2022 • Aysim Toker, Lukas Kondmann, Mark Weber, Marvin Eisenberger, Andrés Camero, Jingliang Hu, Ariadna Pregel Hoderlein, Çağlar Şenaras, Timothy Davis, Daniel Cremers, Giovanni Marchisio, Xiao Xiang Zhu, Laura Leal-Taixé

These observations are paired with pixel-wise monthly semantic segmentation labels of 7 land use and land cover (LULC) classes.

Earth Observation Semantic Segmentation +2

DeepLab2: A TensorFlow Library for Deep Labeling

4 code implementations • 17 Jun 2021 • Mark Weber, Huiyu Wang, Siyuan Qiao, Jun Xie, Maxwell D. Collins, Yukun Zhu, Liangzhe Yuan, Dahun Kim, Qihang Yu, Daniel Cremers, Laura Leal-Taixe, Alan L. Yuille, Florian Schroff, Hartwig Adam, Liang-Chieh Chen

DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a state-of-the-art and easy-to-use TensorFlow codebase for general dense pixel prediction problems in computer vision.

4D Panoptic LiDAR Segmentation

1 code implementation • CVPR 2021 • Mehmet Aygün, Aljoša Ošep, Mark Weber, Maxim Maximov, Cyrill Stachniss, Jens Behley, Laura Leal-Taixé

In this paper, we propose 4D panoptic LiDAR segmentation to assign a semantic class and a temporally-consistent instance ID to a sequence of 3D points.

4D Panoptic Segmentation Benchmarking +4

STEP: Segmenting and Tracking Every Pixel

1 code implementation • 23 Feb 2021 • Mark Weber, Jun Xie, Maxwell Collins, Yukun Zhu, Paul Voigtlaender, Hartwig Adam, Bradley Green, Andreas Geiger, Bastian Leibe, Daniel Cremers, Aljoša Ošep, Laura Leal-Taixé, Liang-Chieh Chen

The task of assigning semantic classes and track identities to every pixel in a video is called video panoptic segmentation.

Segmentation Video Panoptic Segmentation

Single-Shot Panoptic Segmentation

no code implementations • 2 Nov 2019 • Mark Weber, Jonathon Luiten, Bastian Leibe

We present a novel end-to-end single-shot method that segments countable object instances (things) as well as background regions (stuff) into a non-overlapping panoptic segmentation at almost video frame rate.

Instance Segmentation Object +4

Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

1 code implementation • 31 Jul 2019 • Mark Weber, Giacomo Domeniconi, Jie Chen, Daniel Karl I. Weidele, Claudio Bellei, Tom Robinson, Charles E. Leiserson

We contribute the Elliptic Data Set, a time series graph of over 200K Bitcoin transactions (nodes), 234K directed payment flows (edges), and 166 node features, including ones based on non-public data; to our knowledge, this is the largest labelled transaction data set publicly available in any cryptocurrency.

Binary Classification Time Series Analysis

Visual Person Understanding through Multi-Task and Multi-Dataset Learning

no code implementations • 7 Jun 2019 • Kilian Pfeiffer, Alexander Hermans, István Sárándi, Mark Weber, Bastian Leibe

We address the problem of learning a single model for person re-identification, attribute classification, body part segmentation, and pose estimation.

Attribute General Classification +3

4D Generic Video Object Proposals

1 code implementation • 26 Jan 2019 • Aljosa Osep, Paul Voigtlaender, Mark Weber, Jonathon Luiten, Bastian Leibe

Many high-level video understanding methods require input in the form of object proposals.

Instance Segmentation Object +2

Scalable Graph Learning for Anti-Money Laundering: A First Look

2 code implementations • 30 Nov 2018 • Mark Weber, Jie Chen, Toyotaro Suzumura, Aldo Pareja, Tengfei Ma, Hiroki Kanezashi, Tim Kaler, Charles E. Leiserson, Tao B. Schardl

Organized crime inflicts human suffering on a genocidal scale: the Mexican drug cartels have murdered 150, 000 people since 2006, upwards of 700, 000 people per year are "exported" in a human trafficking industry enslaving an estimated 40 million people.

Graph Learning