66 citations · 216 across the 50 of their papers we have counts for
14 papers · 2 filters
Deformable 3D Gaussian Splatting for Animatable Human Avatars
HyunJun Jung, Nikolas Brasch, Jifei Song +5
Recent advances in neural radiance fields enable novel view synthesis of photo-realistic images in dynamic settings, which can be applied to scenarios with human animation. Commonl…
S2P3: Self-Supervised Polarimetric Pose Prediction
Patrick Ruhkamp, Daoyi Gao, Nassir Navab +1
This paper proposes the first self-supervised 6D object pose prediction from multimodal RGB+polarimetric images. The novel training paradigm comprises 1) a physical model to extrac…
RaDialog: A Large Vision-Language Model for Radiology Report Generation and Conversational Assistance
Chantal Pellegrini, Ege Özsoy, Benjamin Busam +2
Conversational AI tools that can generate and discuss clinically correct radiology reports for a given medical image have the potential to transform radiology. Such a human-in-the-…
SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimation
Yamei Chen, Yan Di, Guangyao Zhai +6
Category-level object pose estimation, aiming to predict the 6D pose and 3D size of objects from known categories, typically struggles with large intra-class shape variation. Exist…
RIDE: Self-Supervised Learning of Rotation-Equivariant Keypoint Detection and Invariant Description for Endoscopy
Mert Asim Karaoglu, Viktoria Markova, Nassir Navab +2
Unlike in natural images, in endoscopy there is no clear notion of an up-right camera orientation. Endoscopic videos therefore often contain large rotational motions, which require…
DynaMoN: Motion-Aware Fast and Robust Camera Localization for Dynamic Neural Radiance Fields
Nicolas Schischka, Hannah Schieber, Mert Asim Karaoglu +6
The accurate reconstruction of dynamic scenes with neural radiance fields is significantly dependent on the estimation of camera poses. Widely used structure-from-motion pipelines…
3D Adversarial Augmentations for Robust Out-of-Domain Predictions
Alexander Lehner, Stefano Gasperini, Alvaro Marcos-Ramiro +4
Since real-world training datasets cannot properly sample the long tail of the underlying data distribution, corner cases and rare out-of-domain samples can severely hinder the per…
Polarimetric Information for Multi-Modal 6D Pose Estimation of Photometrically Challenging Objects with Limited Data
Patrick Ruhkamp, Daoyi Gao, HyunJun Jung +2
6D pose estimation pipelines that rely on RGB-only or RGB-D data show limitations for photometrically challenging objects with e.g. textureless surfaces, reflections or transparenc…
Multi-Modal Dataset Acquisition for Photometrically Challenging Object
HyunJun Jung, Patrick Ruhkamp, Nassir Navab +1
This paper addresses the limitations of current datasets for 3D vision tasks in terms of accuracy, size, realism, and suitable imaging modalities for photometrically challenging ob…
DisguisOR: Holistic Face Anonymization for the Operating Room
Lennart Bastian, Tony Danjun Wang, Tobias Czempiel +2
Purpose: Recent advances in Surgical Data Science (SDS) have contributed to an increase in video recordings from hospital environments. While methods such as surgical workflow reco…
CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graph Diffusion
Guangyao Zhai, Evin Pınar Örnek, Shun-Cheng Wu +4
Controllable scene synthesis aims to create interactive environments for various industrial use cases. Scene graphs provide a highly suitable interface to facilitate these applicat…
IPCC-TP: Utilizing Incremental Pearson Correlation Coefficient for Joint Multi-Agent Trajectory Prediction
Dekai Zhu, Guangyao Zhai, Yan Di +6
Reliable multi-agent trajectory prediction is crucial for the safe planning and control of autonomous systems. Compared with single-agent cases, the major challenge in simultaneous…
S3M: Scalable Statistical Shape Modeling through Unsupervised Correspondences
Lennart Bastian, Alexander Baumann, Emily Hoppe +5
Statistical shape models (SSMs) are an established way to represent the anatomy of a population with various clinically relevant applications. However, they typically require domai…
Location-Free Scene Graph Generation
Ege Özsoy, Felix Holm, Mahdi Saleh +4
Scene Graph Generation (SGG) is a visual understanding task, aiming to describe a scene as a graph of entities and their relationships with each other. Existing works rely on locat…