263 citations · 304 across the 9 of their papers we have counts for
13 papers
CryoChains: Heterogeneous Reconstruction of Molecular Assembly of Semi-flexible Chains from Cryo-EM Images
Bongjin Koo, Julien Martel, Ariana Peck +3
Cryogenic electron microscopy (cryo-EM) has transformed structural biology by allowing to reconstruct 3D biomolecular structures up to near-atomic resolution. However, the 3D recon…
Amortized Inference for Heterogeneous Reconstruction in Cryo-EM
Axel Levy, Gordon Wetzstein, Julien Martel +2
Cryo-electron microscopy (cryo-EM) is an imaging modality that provides unique insights into the dynamics of proteins and other building blocks of life. The algorithmic challenge o…
Heterogeneous reconstruction of deformable atomic models in Cryo-EM
Youssef Nashed, Ariana Peck, Julien Martel +6
Cryogenic electron microscopy (cryo-EM) provides a unique opportunity to study the structural heterogeneity of biomolecules. Being able to explain this heterogeneity with atomic mo…
Learning Spatially Varying Pixel Exposures for Motion Deblurring
Cindy M. Nguyen, Julien N. P. Martel, Gordon Wetzstein
Computationally removing the motion blur introduced by camera shake or object motion in a captured image remains a challenging task in computational photography. Deblurring methods…
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images
Axel Levy, Frédéric Poitevin, Julien Martel +6
Cryo-electron microscopy (cryo-EM) has become a tool of fundamental importance in structural biology, helping us understand the basic building blocks of life. The algorithmic chall…
MantissaCam: Learning Snapshot High-dynamic-range Imaging with Perceptually-based In-pixel Irradiance Encoding
Haley M. So, Julien N. P. Martel, Piotr Dudek +1
The ability to image high-dynamic-range (HDR) scenes is crucial in many computer vision applications. The dynamic range of conventional sensors, however, is fundamentally limited b…
ACORN: Adaptive Coordinate Networks for Neural Scene Representation
Julien N. P. Martel, David B. Lindell, Connor Z. Lin +3
Neural representations have emerged as a new paradigm for applications in rendering, imaging, geometric modeling, and simulation. Compared to traditional representations such as me…
Time-Multiplexed Coded Aperture Imaging: Learned Coded Aperture and Pixel Exposures for Compressive Imaging Systems
Edwin Vargas, Julien N. P. Martel, Gordon Wetzstein +1
Compressive imaging using coded apertures (CA) is a powerful technique that can be used to recover depth, light fields, hyperspectral images and other quantities from a single snap…
AutoInt: Automatic Integration for Fast Neural Volume Rendering
David B. Lindell, Julien N. P. Martel, Gordon Wetzstein
Numerical integration is a foundational technique in scientific computing and is at the core of many computer vision applications. Among these applications, neural volume rendering…
Implicit Neural Representations with Periodic Activation Functions
Vincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman +2
Implicitly defined, continuous, differentiable signal representations parameterized by neural networks have emerged as a powerful paradigm, offering many possible benefits over con…
Event Based, Near Eye Gaze Tracking Beyond 10,000Hz
Anastasios N. Angelopoulos, Julien N. P. Martel, Amit P. S. Kohli +2
The cameras in modern gaze-tracking systems suffer from fundamental bandwidth and power limitations, constraining data acquisition speed to 300 Hz realistically. This obstructs the…
Estimation of Z-Thickness and XY-Anisotropy of Electron Microscopy Images using Gaussian Processes
Thanuja D. Ambegoda, Julien N. P. Martel, Jozef Adamcik +2
Serial section electron microscopy (ssEM) is a widely used technique for obtaining volumetric information of biological tissues at nanometer scale. However, accurate 3D reconstruct…
Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor
Sebastian Glatz, Julien N. P. Martel, Raphaela Kreiser +2
Neuromorphic computing is a new paradigm for design of both the computing hardware and algorithms inspired by biological neural networks. The event-based nature and the inherent pa…