Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR1.2k papers
- The University of TokyoJP948 papers
- Excellence Cluster UniverseDE902 papers
- University of BonnDE857 papers
- Max Planck Institute for PhysicsDE848 papers
- Ludwig-Maximilians-Universität MünchenDE836 papers
- Lawrence Berkeley National LaboratoryUS774 papers
- University of CopenhagenDK774 papers
- Commissariat à l'Énergie Atomique et aux Énergies AlternativesFR757 papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR745 papers
- European Organization for Nuclear ResearchCH705 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di TorinoIT682 papers
46 papers · 2 filters
Invariant Attribute Profiles: A Spatial-Frequency Joint Feature Extractor for Hyperspectral Image Classification
Danfeng Hong, Xin Wu, Pedram Ghamisi +3
Up to the present, an enormous number of advanced techniques have been developed to enhance and extract the spatially semantic information in hyperspectral image processing and ana…
Learning Shared Cross-modality Representation Using Multispectral-LiDAR and Hyperspectral Data
Danfeng Hong, Jocelyn Chanussot, Naoto Yokoya +2
Due to the ever-growing diversity of the data source, multi-modality feature learning has attracted more and more attention. However, most of these methods are designed by jointly…
Signal Clustering with Class-independent Segmentation
Stefano Gasperini, Magdalini Paschali, Carsten Hopke +2
Radar signals have been dramatically increasing in complexity, limiting the source separation ability of traditional approaches. In this paper we propose a Deep Learning-based clus…
Building Segmentation through a Gated Graph Convolutional Neural Network with Deep Structured Feature Embedding
Yilei Shi, Qingyu Li, Xiao Xiang Zhu
Automatic building extraction from optical imagery remains a challenge due to, for example, the complexity of building shapes. Semantic segmentation is an efficient approach for th…
Rolling-Shutter Modelling for Direct Visual-Inertial Odometry
David Schubert, Nikolaus Demmel, Lukas von Stumberg +2
We present a direct visual-inertial odometry (VIO) method which estimates the motion of the sensor setup and sparse 3D geometry of the environment based on measurements from a roll…
Efficient Derivative Computation for Cumulative B-Splines on Lie Groups
Christiane Sommer, Vladyslav Usenko, David Schubert +2
Continuous-time trajectory representation has recently gained popularity for tasks where the fusion of high-frame-rate sensors and multiple unsynchronized devices is required. Lie…
You Only Watch Once: A Unified CNN Architecture for Real-Time Spatiotemporal Action Localization
Okan Köpüklü, Xiangyu Wei, Gerhard Rigoll
Spatiotemporal action localization requires the incorporation of two sources of information into the designed architecture: (1) temporal information from the previous frames and (2…
Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmark
Ke Li, Gang Wan, Gong Cheng +2
Substantial efforts have been devoted more recently to presenting various methods for object detection in optical remote sensing images. However, the current survey of datasets and…
Invasiveness Prediction of Pulmonary Adenocarcinomas Using Deep Feature Fusion Networks
Xiang Li, Jiechao Ma, Hongwei Li
Early diagnosis of pathological invasiveness of pulmonary adenocarcinomas using computed tomography (CT) imaging would alter the course of treatment of adenocarcinomas and subseque…
Learn to Estimate Labels Uncertainty for Quality Assurance
Agnieszka Tomczack, Nassir Navab, Shadi Albarqouni
Deep Learning sets the state-of-the-art in many challenging tasks showing outstanding performance in a broad range of applications. Despite its success, it still lacks robustness h…
Learn to Segment Organs with a Few Bounding Boxes
Abhijeet Parida, Arianne Tran, Nassir Navab +1
Semantic segmentation is an import task in the medical field to identify the exact extent and orientation of significant structures like organs and pathology. Deep neural networks…
Tracking Holistic Object Representations
Axel Sauer, Elie Aljalbout, Sami Haddadin
Recent advances in visual tracking are based on siamese feature extractors and template matching. For this category of trackers, latest research focuses on better feature embedding…
Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation
Yuxing Xie, Jiaojiao Tian, Xiao Xiang Zhu
3D Point Cloud Semantic Segmentation (PCSS) is attracting increasing interest, due to its applicability in remote sensing, computer vision and robotics, and due to the new possibil…
To Learn or Not to Learn: Visual Localization from Essential Matrices
Qunjie Zhou, Torsten Sattler, Marc Pollefeys +1
Visual localization is the problem of estimating a camera within a scene and a key component in computer vision applications such as self-driving cars and Mixed Reality. State-of-t…
Domain-Specific Priors and Meta Learning for Few-Shot First-Person Action Recognition
Huseyin Coskun, Zeeshan Zia, Bugra Tekin +4
The lack of large-scale real datasets with annotations makes transfer learning a necessity for video activity understanding. We aim to develop an effective method for few-shot tran…
Relation Network for Multi-label Aerial Image Classification
Yuansheng Hua, Lichao Mou, Xiao Xiang Zhu
Multi-label classification plays a momentous role in perceiving intricate contents of an aerial image and triggers several related studies over the last years. However, most of the…
MIMA: MAPPER-Induced Manifold Alignment for Semi-Supervised Fusion of Optical Image and Polarimetric SAR Data
Jingliang Hu, Danfeng Hong, Xiao Xiang Zhu
Multi-modal data fusion has recently been shown promise in classification tasks in remote sensing. Optical data and radar data, two important yet intrinsically different data sourc…
Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks
Thomas Brunner, Frederik Diehl, Alois Knoll
Many optimization methods for generating black-box adversarial examples have been proposed, but the aspect of initializing said optimizers has not been considered in much detail. W…
Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection
Xin Wu, Danfeng Hong, Jocelyn Chanussot +3
Geospatial object detection of remote sensing imagery has been attracting an increasing interest in recent years, due to the rapid development in spaceborne imaging. Most of previo…
Query-guided End-to-End Person Search
Bharti Munjal, Sikandar Amin, Federico Tombari +1
Person search has recently gained attention as the novel task of finding a person, provided as a cropped sample, from a gallery of non-cropped images, whereby several other people…
Deferred Neural Rendering: Image Synthesis using Neural Textures
Justus Thies, Michael Zollhöfer, Matthias Nießner
The modern computer graphics pipeline can synthesize images at remarkable visual quality; however, it requires well-defined, high-quality 3D content as input. In this work, we expl…
Late or Earlier Information Fusion from Depth and Spectral Data? Large-Scale Digital Surface Model Refinement by Hybrid-cGAN
Ksenia Bittner, Marco Körner, Peter Reinartz
We present the workflow of a DSM refinement methodology using a Hybrid-cGAN where the generative part consists of two encoders and a common decoder which blends the spectral and he…
Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope
Tolga Birdal, Umut Şimşekli
We present an entirely new geometric and probabilistic approach to synchronization of correspondences across multiple sets of objects or images. In particular, we present two algor…
3D Object Instance Recognition and Pose Estimation Using Triplet Loss with Dynamic Margin
Sergey Zakharov, Wadim Kehl, Benjamin Planche +2
In this paper, we address the problem of 3D object instance recognition and pose estimation of localized objects in cluttered environments using convolutional neural networks. Insp…