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From the 8 of 272 papers with an AI index.

most citedSEOBNRv5PHM: Next generation of accurate and efficient multipolar precessing-spin effective-one-body waveforms for binary black holes

159 citations

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cs.CV2026

CalibBEV: LiDAR-Camera Calibration via BEV Alignment

Filippo D'Addeo, Lorenzo Cipelli, Adriano Cardace +3

We present CalibBEV, a novel Bird's Eye View (BEV) alignment approach for LiDAR-camera calibration. Our method unifies LiDAR and camera data into a shared 3D spatial representation…

cs.CV2026

NeuroQA: A Large-Scale Image-Grounded Benchmark for 3D Brain MRI Understanding

Mohammad H. Abbasi, Favour Nerrise, Shaurnav Ghosh +12

We present NeuroQA, a large-scale benchmark for visual question answering in 3D brain magnetic resonance imaging (MRI), with 56,953 QA pairs from 12,977 subjects across 12 datasets…

cs.CV2026

GeoSAE: Geometric Prior-Guided Layer-Wise Sparse Autoencoder Annotation of Brain MRI Foundation Models

Favour Nerrise, Lucy Yin, Mohammad H. Abbasi +2

Brain MRI foundation models learn rich representations of anatomy, but interpreting what clinical information they encode remains an open problem. Standard sparse autoencoders (SAE…

cs.CV2026

UniVidX: A Unified Multimodal Framework for Versatile Video Generation via Diffusion Priors

Houyuan Chen, Hong Li, Xianghao Kong +8

Recent progress has shown that video diffusion models (VDMs) can be repurposed for diverse multimodal graphics tasks. However, existing methods often train separate models for each…

cs.CV20261 cited

Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction

Sara Fridovich-Keil, Fabrizio Valdivia, Gordon Wetzstein +2

In computed tomography (CT), the forward model consists of a linear Radon transform followed by an exponential nonlinearity based on the attenuation of light according to the Beer-…

cs.CV202633 cited

Latent diffusion models for parameterization and data assimilation of facies-based geomodels

Guido Di Federico, Louis J. Durlofsky

Geological parameterization entails the representation of a geomodel using a small set of latent variables and a mapping from these variables to grid-block properties such as poros…