39 citations · 65 across the 12 of their papers we have counts for
13 papers
Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections
Gil Lifshits, Igal Bilik, Gilad Katz
Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, which typically struggle with com…
A Comparative Study of Vision Transformers and CNNs for Few-Shot Rigid Transformation and Fundamental Matrix Estimation
Alon Kaya, Igal Bilik, Inna Stainvas
Vision-transformers (ViTs) and large-scale convolution-neural-networks (CNNs) have reshaped computer vision through pretrained feature representations that enable strong transfer l…
Tangential Velocity Estimation Using Near-Field Automotive Radar Model
Michael Shifrin, Joseph Tabrikian, Igal Bilik
This work investigates the problem of tangential velocity estimation in automotive radar systems, addressing the limitations of conventionally considered models. Conventional autom…
RGBX-DiffusionDet: A Framework for Multi-Modal RGB-X Object Detection Using DiffusionDet
Eliraz Orfaig, Inna Stainvas, Igal Bilik
This work introduces RGBX-DiffusionDet, an object detection framework extending the DiffusionDet model to fuse the heterogeneous 2D data (X) with RGB imagery via an adaptive multim…
A Hybrid Approach for Extending Automotive Radar Operation to NLOS Urban Scenarios
Aviran Gal, Igal Bilik
Automotive radar is a key component of sensing suites in autonomous driving (AD) and advanced driver-assist systems (ADAS). However, limited line-of-sight (LOS) significantly reduc…
SuperResolution Radar Gesture Recognitio
Netanel Blumenfeld, Inna Stainvas, Igal Bilik
"This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible." Driver's int…
Enhanced Automotive Object Detection via RGB-D Fusion in a DiffusionDet Framework
Eliraz Orfaig, Inna Stainvas, Igal Bilik
Vision-based autonomous driving requires reliable and efficient object detection. This work proposes a DiffusionDet-based framework that exploits data fusion from the monocular cam…
MCRB on DOA Estimation for Automotive MIMO Radar in the Presence of Multipath
Moshe Levy-Israel, Igal Bilik, Joseph Tabrikian
Autonomous driving and advanced active safety features require accurate high-resolution sensing capabilities. Automotive radars are the key component of the vehicle sensing suit. H…
Neural Network-Based DOA Estimation in the Presence of Non-Gaussian Interference
Stefan Feintuch, Joseph Tabrikian, Igal Bilik +1
This work addresses the problem of direction-of-arrival (DOA) estimation in the presence of non-Gaussian, heavy-tailed, and spatially-colored interference. Conventionally, the inte…
Neural Network-Based Multi-Target Detection within Correlated Heavy-Tailed Clutter
Stefan Feintuch, Haim H. Permuter, Igal Bilik +1
This work addresses the problem of range-Doppler multiple target detection in a radar system in the presence of slow-time correlated and heavy-tailed distributed clutter. Conventio…
Deep Radar Detector
Daniel Brodeski, Igal Bilik, Raja Giryes
While camera and LiDAR processing have been revolutionized since the introduction of deep learning, radar processing still relies on classical tools. In this paper, we introduce a…
Pedestrian Motion Direction Estimation Using Simulated Automotive MIMO Radar
Petro Khomchuk, Inna Stainvas, Igal Bilik
Micro-Doppler-based target classification capabilities of the automotive radars can provide high reliability and short latency to the future active safety automotive features. A la…
Performance Analysis of Target Parameters Estimation Using Multiple Widely Separated Antenna Arrays
Peter Khomchuk, Igal Bilik, Rick S. Blum
Target parameter estimation performance is investigated for a radar employing a set of widely separated transmitting and receiving antenna arrays. Cases with multiple extended targ…