相关论文: Dynamic Black-hole Emission Tomography with Physic…

We present an improved and expanded simply parameterized phenomenological model of the broad line region (BLR) in active galactic nuclei (AGN) for modeling reverberation mapping data. By modeling reverberation mapping data directly, we can…

A key challenge in imaging supermassive black holes is disentangling gravitational effects from plasma physics in order to accurately determine spacetime properties, particularly black hole spin. In this Letter, we present a fully covariant…

Neural Radiance Fields (NeRFs) can be dramatically accelerated by spatial grid representations. However, they do not explicitly reason about scale and so introduce aliasing artifacts when reconstructing scenes captured at different camera…

Coronagraphic observations enable direct monitoring of coronal mass ejections (CMEs) through scattered light from free electrons, but determining the 3D plasma distribution from 2D imaging data is challenging due to the optically-thin…

We study initially unbound systems of two black holes using numerical relativity (NR) simulations performed with GR-Athena++. We focus on regions of the parameter space close to the transition from scatterings to dynamical captures,…

We present a stellar dynamical estimate of the black hole (BH) mass in the Seyfert 1 galaxy, NGC 4151. We analyze ground-based spectroscopy as well as imaging data from the ground and space, and we construct 3-integral axisymmetric models…

Volumetric reconstruction of dynamic scenes is an important problem in computer vision. It is especially challenging in poor lighting and with fast motion. This is partly due to limitations of RGB cameras: To capture frames under low…

Dynamical capture is a possible formation channel for BBH mergers leading to highly eccentric merger dynamics and to gravitational wave (GW) signals that are morphologically different from those of quasi-circular mergers. The future…

Recently, Neural Radiance Fields (NeRF) has shown promising performances on reconstructing 3D scenes and synthesizing novel views from a sparse set of 2D images. Albeit effective, the performance of NeRF is highly influenced by the quality…

The Event Horizon Telescope (EHT) captured the first images of a black hole using Very Long Baseline Interferometry (VLBI). In the near future, extensions of the EHT such as the Black Hole Explorer (BHEX) will allow access to finer-scale…

Modeling 4D scenes requires capturing both spatial structure and temporal motion, which is challenging due to the need for physically consistent representations of complex rigid and non-rigid motions. Existing approaches mainly rely on…

By consideration of a Einstein-dilaton non-linear charged gravitating system, it has been shown that this theory is confronted with the problem of indeterminacy. It means that the number of independent differential equations is one less…

The stellar dynamic-based black hole mass measurements of M87 are twice that determined via ionized gas kinematics; the former is closer to the estimation from the diameter of the gravitationally-lensed ring around the black hole. Using…

The Event Horizon Telescope (EHT) provides a unique opportunity to probe the physics of supermassive black holes through Very Large Baseline Interferometry (VLBI), such as the existence of the event horizon, the accretion processes as well…

Precise scene understanding is key for most robot monitoring and intervention tasks in agriculture. In this work we present PAg-NeRF which is a novel NeRF-based system that enables 3D panoptic scene understanding. Our representation is…

Neural implicit reconstruction via volume rendering has demonstrated its effectiveness in recovering dense 3D surfaces. However, it is non-trivial to simultaneously recover meticulous geometry and preserve smoothness across regions with…

We present Non-Rigid Neural Radiance Fields (NR-NeRF), a reconstruction and novel view synthesis approach for general non-rigid dynamic scenes. Our approach takes RGB images of a dynamic scene as input (e.g., from a monocular video…

We present a method for reconstructing a clear Neural Radiance Field (NeRF) even with fast camera motions. To address blur artifacts, we leverage both (blurry) RGB images and event camera data captured in a binocular configuration.…

Pose estimation of 3D objects in monocular images is a fundamental and long-standing problem in computer vision. Existing deep learning approaches for 6D pose estimation typically rely on the assumption of availability of 3D object models…

Asynchronously operating event cameras find many applications due to their high dynamic range, vanishingly low motion blur, low latency and low data bandwidth. The field saw remarkable progress during the last few years, and existing…