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cs.CV2026

Low Light Image Enhancement Challenge at NTIRE 2026

George Ciubotariu, Sharif S M A, Abdur Rehman +90

This paper presents a comprehensive review of the NTIRE 2026 Low Light Image Enhancement Challenge, highlighting the proposed solutions and final results. The objective of this cha…

cs.CV2026

C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion

Yuval Haitman, Amit Efraim, Joseph M. Francos

We introduce C-GenReg, a training-free framework for 3D point cloud registration that leverages the complementary strengths of world-scale generative priors and registration-orient…

cs.CV2025

DoppDrive: Doppler-Driven Temporal Aggregation for Improved Radar Object Detection

Yuval Haitman, Oded Bialer

Radar-based object detection is essential for autonomous driving due to radar's long detection range. However, the sparsity of radar point clouds, especially at long range, poses c…

cs.CV2024

UMERegRobust - Universal Manifold Embedding Compatible Features for Robust Point Cloud Registration

Yuval Haitman, Amit Efraim, Joseph M. Francos

In this paper, we adopt the Universal Manifold Embedding (UME) framework for the estimation of rigid transformations and extend it, so that it can accommodate scenarios involving p…

cs.CV2024

RadSimReal: Bridging the Gap Between Synthetic and Real Data in Radar Object Detection With Simulation

Oded Bialer, Yuval Haitman

Object detection in radar imagery with neural networks shows great potential for improving autonomous driving. However, obtaining annotated datasets from real radar images, crucial…

cs.CV2024

BoostRad: Enhancing Object Detection by Boosting Radar Reflections

Yuval Haitman, Oded Bialer

Automotive radars have an important role in autonomous driving systems. The main challenge in automotive radar detection is the radar's wide point spread function (PSF) in the angu…