3 citations · 9 across the 9 of their papers we have counts for
10 papers
Autonomous Discovery of Wireless Communications Algorithms
Fayçal Aït Aoudia, Jakob Hoydis, Sebastian Cammerer +4
Large language model (LLM)-driven evolutionary search is an emerging algorithm-discovery paradigm that has already produced novel results in several scientific fields. Yet its appl…
Neural Harmonic Textures for High-Quality Primitive Based Neural Reconstruction
Jorge Condor, Nicolas Moenne-Loccoz, Merlin Nimier-David +3
Primitive-based methods such as 3D Gaussian Splatting have recently become the state-of-the-art for novel-view synthesis and related reconstruction tasks. Compared to neural fields…
Stochastic Preconditioning for Neural Field Optimization
Selena Ling, Merlin Nimier-David, Alec Jacobson +1
Neural fields are a highly effective representation across visual computing. This work observes that fitting these fields is greatly improved by incorporating spatial stochasticity…
GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control
Xuanchi Ren, Tianchang Shen, Jiahui Huang +7
We present GEN3C, a generative video model with precise Camera Control and temporal 3D Consistency. Prior video models already generate realistic videos, but they tend to leverage…
Radiance Surfaces: Optimizing Surface Representations with a 5D Radiance Field Loss
Ziyi Zhang, Nicolas Roussel, Thomas Müller +4
We present a fast and simple technique to convert images into a radiance surface-based scene representation. Building on existing radiance volume reconstruction algorithms, we intr…
Photorealistic Object Insertion with Diffusion-Guided Inverse Rendering
Ruofan Liang, Zan Gojcic, Merlin Nimier-David +4
The correct insertion of virtual objects in images of real-world scenes requires a deep understanding of the scene's lighting, geometry and materials, as well as the image formatio…
Compact Neural Graphics Primitives with Learned Hash Probing
Towaki Takikawa, Thomas Müller, Merlin Nimier-David +4
Neural graphics primitives are faster and achieve higher quality when their neural networks are augmented by spatial data structures that hold trainable features arranged in a grid…
Learning Radio Environments by Differentiable Ray Tracing
Jakob Hoydis, Fayçal Aït Aoudia, Sebastian Cammerer +4
Ray tracing (RT) is instrumental in 6G research in order to generate spatially-consistent and environment-specific channel impulse responses (CIRs). While acquiring accurate scene…
Adaptive Shells for Efficient Neural Radiance Field Rendering
Zian Wang, Tianchang Shen, Merlin Nimier-David +6
Neural radiance fields achieve unprecedented quality for novel view synthesis, but their volumetric formulation remains expensive, requiring a huge number of samples to render high…
Sionna RT: Differentiable Ray Tracing for Radio Propagation Modeling
Jakob Hoydis, Fayçal Aït Aoudia, Sebastian Cammerer +4
Sionna is a GPU-accelerated open-source library for link-level simulations based on TensorFlow. Since release v0.14 it integrates a differentiable ray tracer (RT) for the simulatio…