no code implementations • 25 Jan 2023 • Magdalena Wysocki, Mohammad Farid Azampour, Christine Eilers, Benjamin Busam, Mehrdad Salehi, Nassir Navab
In our work, we discuss direction-dependent changes in the scene and show that a physics-inspired rendering improves the fidelity of US image synthesis.
no code implementations • 17 Jan 2023 • Shervin Dehghani, Michael Sommersperger, Peiyao Zhang, Alejandro Martin-Gomez, Benjamin Busam, Peter Gehlbach, Nassir Navab, M. Ali Nasseri, Iulian Iordachita
In this work, we propose a framework for autonomous robotic navigation for subretinal injection, based on intelligent real-time processing of iOCT volumes.
no code implementations • 25 Dec 2022 • Hanzhi Chen, Fabian Manhardt, Nassir Navab, Benjamin Busam
In this paper, we introduce neural texture learning for 6D object pose estimation from synthetic data and a few unlabelled real images.
no code implementations • 20 Dec 2022 • HyunJun Jung, Shun-Cheng Wu, Patrick Ruhkamp, Hannah Schieber, Pengyuan Wang, Giulia Rizzoli, Hongcheng Zhao, Sven Damian Meier, Daniel Roth, Nassir Navab, Benjamin Busam
Estimating the 6D pose of objects is one of the major fields in 3D computer vision.
no code implementations • 2 Nov 2022 • Yongzhi Su, Yan Di, Fabian Manhardt, Guangyao Zhai, Jason Rambach, Benjamin Busam, Didier Stricker, Federico Tombari
Despite monocular 3D object detection having recently made a significant leap forward thanks to the use of pre-trained depth estimators for pseudo-LiDAR recovery, such two-stage methods typically suffer from overfitting and are incapable of explicitly encapsulating the geometric relation between depth and object bounding box.
no code implementations • 27 Sep 2022 • Hao Yu, Ji Hou, Zheng Qin, Mahdi Saleh, Ivan Shugurov, Kai Wang, Benjamin Busam, Slobodan Ilic
More specifically, 3D structures of the whole frame are first represented by our global PPF signatures, from which structural descriptors are learned to help geometric descriptors sense the 3D world beyond local regions.
no code implementations • 26 Sep 2022 • Guangyao Zhai, Dianye Huang, Shun-Cheng Wu, HyunJun Jung, Yan Di, Fabian Manhardt, Federico Tombari, Nassir Navab, Benjamin Busam
6-DoF robotic grasping is a long-lasting but unsolved problem.
no code implementations • 12 Sep 2022 • Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt, Nassir Navab, Benjamin Busam, Federico Tombari
In this work, we propose the necessary step to extend segmentation with a new task which we term holistic segmentation.
no code implementations • 5 Aug 2022 • Xue Hu, Xinghui Li, Benjamin Busam, Yiren Zhou, Ales Leonardis, Shanxin Yuan
Specifically, we focus on human appearance and learn implicit pose, shape and garment representations of dressed humans from RGB images.
no code implementations • 31 Jul 2022 • Guangyao Zhai, Yu Zheng, Ziwei Xu, Xin Kong, Yong liu, Benjamin Busam, Yi Ren, Nassir Navab, Zhengyou Zhang
In this paper, we introduce DA$^2$, the first large-scale dual-arm dexterity-aware dataset for the generation of optimal bimanual grasping pairs for arbitrary large objects.
no code implementations • 31 Jul 2022 • Mahdi Saleh, Yige Wang, Nassir Navab, Benjamin Busam, Federico Tombari
The proposed hierarchical model achieves state-of-the-art shape classification in mean accuracy and yields results on par with the previous segmentation methods while requiring significantly fewer computations.
no code implementations • 9 Jun 2022 • Shervin Dehghani, Benjamin Busam, Nassir Navab, Ali Nasseri
Despite its broad availability, volumetric information acquisition from Bright-Field Microscopy (BFM) is inherently difficult due to the projective nature of the acquisition process.
no code implementations • CVPR 2022 • Pengyuan Wang, HyunJun Jung, Yitong Li, Siyuan Shen, Rahul Parthasarathy Srikanth, Lorenzo Garattoni, Sven Meier, Nassir Navab, Benjamin Busam
Object pose estimation is crucial for robotic applications and augmented reality.
no code implementations • 9 May 2022 • HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai, Nikolas Brasch, Yitong Li, Yannick Verdie, Jifei Song, Yiren Zhou, Anil Armagan, Slobodan Ilic, Ales Leonardis, Benjamin Busam
Depth estimation is a core task in 3D computer vision.
no code implementations • CVPR 2022 • Ivan Shugurov, Fu Li, Benjamin Busam, Slobodan Ilic
We present a novel one-shot method for object detection and 6 DoF pose estimation, that does not require training on target objects.
no code implementations • CVPR 2022 • Yannick Verdié, Jifei Song, Barnabé Mas, Benjamin Busam, Aleš Leonardis, Steven McDonagh
Learning-based depth estimation has witnessed recent progress in multiple directions; from self-supervision using monocular video to supervised methods offering highest accuracy.
1 code implementation • CVPR 2022 • Yongzhi Su, Mahdi Saleh, Torben Fetzer, Jason Rambach, Nassir Navab, Benjamin Busam, Didier Stricker, Federico Tombari
Dense methods also improved pose estimation in the presence of occlusion.
no code implementations • 16 Mar 2022 • Lennart Bastian, Tobias Czempiel, Christian Heiliger, Konrad Karcz, Ulrich Eck, Benjamin Busam, Nassir Navab
Existing datasets from OR room cameras are thus far limited in size or modalities acquired, leaving it unclear which sensor modalities are best suited for tasks such as recognizing surgical action from videos.
no code implementations • 9 Mar 2022 • Fu Li, Hao Yu, Ivan Shugurov, Benjamin Busam, Shaowu Yang, Slobodan Ilic
Pose estimation of 3D objects in monocular images is a fundamental and long-standing problem in computer vision.
no code implementations • CVPR 2022 • Mahdi Saleh, Shun-Cheng Wu, Luca Cosmo, Nassir Navab, Benjamin Busam, Federico Tombari
Shape matching has been a long-studied problem for the computer graphics and vision community.
no code implementations • CVPR 2022 • Alexander Lehner, Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt, Mohammad-Ali Nikouei Mahani, Nassir Navab, Benjamin Busam, Federico Tombari
Despite training only on a standard dataset, such as KITTI, augmenting with our vector fields significantly improves the generalization to differently shaped objects and scenes.
no code implementations • 7 Dec 2021 • HyunJun Jung, Nikolas Brasch, Ales Leonardis, Nassir Navab, Benjamin Busam
Indirect Time-of-Flight (I-ToF) imaging is a widespread way of depth estimation for mobile devices due to its small size and affordable price.
no code implementations • 7 Dec 2021 • Daoyi Gao, Yitong Li, Patrick Ruhkamp, Iuliia Skobleva, Magdalena Wysock, HyunJun Jung, Pengyuan Wang, Arturo Guridi, Benjamin Busam
Light has many properties that vision sensors can passively measure.
no code implementations • 6 Dec 2021 • Pengyuan Wang, Fabian Manhardt, Luca Minciullo, Lorenzo Garattoni, Sven Meie, Nassir Navab, Benjamin Busam
We first present a small sequence of RGB-D images displaying a human-object interaction.
no code implementations • 30 Nov 2021 • Shervin Dehghani, Michael Sommersperger, Junjie Yang, Benjamin Busam, Kai Huang, Peter Gehlbach, Iulian Iordachita, Nassir Navab, M. Ali Nasseri
For this purpose, we present a platform for autonomous trocar docking that combines computer vision and a robotic setup.
1 code implementation • NeurIPS 2021 • Hao Yu, Fu Li, Mahdi Saleh, Benjamin Busam, Slobodan Ilic
We study the problem of extracting correspondences between a pair of point clouds for registration.
no code implementations • 15 Oct 2021 • Patrick Ruhkamp, Daoyi Gao, Hanzhi Chen, Nassir Navab, Benjamin Busam
A novel temporal attention mechanism further processes the local geometric information in a global context across consecutive images.
no code implementations • 4 Oct 2021 • Stefano Gasperini, Jan Haug, Mohammad-Ali Nikouei Mahani, Alvaro Marcos-Ramiro, Nassir Navab, Benjamin Busam, Federico Tombari
Estimating the uncertainty of a neural network plays a fundamental role in safety-critical settings.
no code implementations • 10 Aug 2021 • Stefano Gasperini, Patrick Koch, Vinzenz Dallabetta, Nassir Navab, Benjamin Busam, Federico Tombari
While self-supervised monocular depth estimation in driving scenarios has achieved comparable performance to supervised approaches, violations of the static world assumption can still lead to erroneous depth predictions of traffic participants, posing a potential safety issue.
1 code implementation • NeurIPS 2021 • Hao Yu, Fu Li, Mahdi Saleh, Benjamin Busam, Slobodan Ilic
We study the problem of extracting correspondences between a pair of point clouds for registration.
no code implementations • 5 Mar 2021 • Tobias Czempiel, Magdalini Paschali, Daniel Ostler, Seong Tae Kim, Benjamin Busam, Nassir Navab
In this paper we introduce OperA, a transformer-based model that accurately predicts surgical phases from long video sequences.
1 code implementation • 18 Oct 2020 • Mahdi Saleh, Shervin Dehghani, Benjamin Busam, Nassir Navab, Federico Tombari
3D Point clouds are a rich source of information that enjoy growing popularity in the vision community.
no code implementations • 26 Sep 2020 • Benjamin Busam, Hyun Jun Jung, Nassir Navab
We change this paradigm and reformulate the problem as an action decision process where an initial pose is updated in incremental discrete steps that sequentially move a virtual 3D rendering towards the correct solution.
no code implementations • 3 Aug 2020 • Adrian Lopez-Rodriguez, Benjamin Busam, Krystian Mikolajczyk
Depth completion aims to predict a dense depth map from a sparse depth input.
no code implementations • 31 Jul 2020 • Patrick Ruhkamp, Ruiqi Gong, Nassir Navab, Benjamin Busam
Feature based visual odometry and SLAM methods require accurate and fast correspondence matching between consecutive image frames for precise camera pose estimation in real-time.
1 code implementation • 12 May 2020 • Axel Barroso-Laguna, Yannick Verdie, Benjamin Busam, Krystian Mikolajczyk
Local feature extraction remains an active research area due to the advances in fields such as SLAM, 3D reconstructions, or AR applications.
no code implementations • 12 Mar 2020 • Fabian Manhardt, Gu Wang, Benjamin Busam, Manuel Nickel, Sven Meier, Luca Minciullo, Xiangyang Ji, Nassir Navab
Contemporary monocular 6D pose estimation methods can only cope with a handful of object instances.
1 code implementation • CVPR 2020 • Daniel Hernandez-Juarez, Sarah Parisot, Benjamin Busam, Ales Leonardis, Gregory Slabaugh, Steven McDonagh
Firstly, we select a set of candidate scene illuminants in a data-driven fashion and apply them to a target image to generate of set of corrected images.
no code implementations • 29 Sep 2019 • Benjamin Busam, Matthieu Hog, Steven McDonagh, Gregory Slabaugh
Whether to attract viewer attention to a particular object, give the impression of depth or simply reproduce human-like scene perception, shallow depth of field images are used extensively by professional and amateur photographers alike.
no code implementations • 4 Jan 2019 • Tolga Birdal, Benjamin Busam, Nassir Navab, Slobodan Ilic, Peter Sturm
Based upon the idea of aligning the quadric gradients with the surface normals, our first formulation is exact and requires as low as four oriented points.
no code implementations • ICCV 2019 • Fabian Manhardt, Diego Martin Arroyo, Christian Rupprecht, Benjamin Busam, Tolga Birdal, Nassir Navab, Federico Tombari
For each object instance we predict multiple pose and class outcomes to estimate the specific pose distribution generated by symmetries and repetitive textures.
no code implementations • 5 Apr 2018 • Benjamin Busam, Patrick Ruhkamp, Salvatore Virga, Beatrice Lentes, Julia Rackerseder, Nassir Navab, Christoph Hennersperger
Tracking of rotation and translation of medical instruments plays a substantial role in many modern interventions.
no code implementations • CVPR 2018 • Tolga Birdal, Benjamin Busam, Nassir Navab, Slobodan Ilic, Peter Sturm
As opposed to state-of-the-art, where a tailored algorithm treats each primitive type separately, we propose to encapsulate all types in a single robust detection procedure.
no code implementations • 24 Apr 2017 • Benjamin Busam, Tolga Birdal, Nassir Navab
Time-varying, smooth trajectory estimation is of great interest to the vision community for accurate and well behaving 3D systems.