Cover Image

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

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bialer, Oded, Haitman, Yuval
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

BoostRad: Enhancing Object Detection by Boosting Radar Reflections
by: Haitman, Yuval, et al.
Published: (2024)

DoppDrive: Doppler-Driven Temporal Aggregation for Improved Radar Object Detection
by: Haitman, Yuval, et al.
Published: (2025)

Sim2Radar: Toward Bridging the Radar Sim-to-Real Gap with VLM-Guided Scene Reconstruction
by: Bejerano, Emily, et al.
Published: (2026)

Synthetic Data Generation for Bridging Sim2Real Gap in a Production Environment
by: Rawal, Parth, et al.
Published: (2023)

GlovEgo-HOI: Bridging the Synthetic-to-Real Gap for Industrial Egocentric Human-Object Interaction Detection
by: Spoto, Alfio, et al.
Published: (2026)

How Real is CARLAs Dynamic Vision Sensor? A Study on the Sim-to-Real Gap in Traffic Object Detection
by: Tan, Kaiyuan, et al.
Published: (2025)

UMERegRobust - Universal Manifold Embedding Compatible Features for Robust Point Cloud Registration
by: Haitman, Yuval, et al.
Published: (2024)

C-GenReg: Training-Free 3D Point Cloud Registration by Multi-View-Consistent Geometry-to-Image Generation with Probabilistic Modalities Fusion
by: Haitman, Yuval, et al.
Published: (2026)

Synthetic-to-Real Camouflaged Object Detection
by: Luo, Zhihao, et al.
Published: (2025)

Sim-to-Real Fruit Detection Using Synthetic Data: Quantitative Evaluation and Embedded Deployment with Isaac Sim
by: Hutter-Mironovova, Martina
Published: (2026)

Generative AI for Enhanced Wildfire Detection: Bridging the Synthetic-Real Domain Gap
by: Gaba, Satyam
Published: (2025)

Digi2Real: Bridging the Realism Gap in Synthetic Data Face Recognition via Foundation Models
by: George, Anjith, et al.
Published: (2024)

Closing the Visual Sim-to-Real Gap with Object-Composable NeRFs
by: Mishra, Nikhil, et al.
Published: (2024)

Bridging the Sim2Real Gap: Vision Encoder Pre-Training for Visuomotor Policy Transfer
by: Yardi, Yash, et al.
Published: (2025)

RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning
by: Zuo, Jiacheng, et al.
Published: (2025)

High-Fidelity Digital Twins for Bridging the Sim2Real Gap in LiDAR-Based ITS Perception
by: Shahbaz, Muhammad, et al.
Published: (2025)

Mind the Gap Between Synthetic and Real: Utilizing Transfer Learning to Probe the Boundaries of Stable Diffusion Generated Data
by: Hennicke, Leonhard, et al.
Published: (2024)

Bridging the Gap Between Ideal and Real-world Evaluation: Benchmarking AI-Generated Image Detection in Challenging Scenarios
by: Li, Chunxiao, et al.
Published: (2025)

SADGE: Structure and Appearance Domain Gap Estimation of Synthetic and Real Data
by: Bartkowiak, Patryk, et al.
Published: (2026)

CauCLIP: Bridging the Sim-to-Real Gap in Surgical Video Understanding via Causality-Inspired Vision-Language Modeling
by: He, Yuxin, et al.
Published: (2026)

The Impact of Synthetic Data on Object Detection Model Performance: A Comparative Analysis with Real-World Data
by: Bay, Muammer, et al.
Published: (2025)

Benchmarking the Sim-to-Real Gap in Cloth Manipulation
by: Blanco-Mulero, David, et al.
Published: (2023)

Stable-Sim2Real: Exploring Simulation of Real-Captured 3D Data with Two-Stage Depth Diffusion
by: Xu, Mutian, et al.
Published: (2025)

SparseRadNet: Sparse Perception Neural Network on Subsampled Radar Data
by: Wu, Jialong, et al.
Published: (2024)

RadarSim: Simulating Single-Chip Radar via Multimodal Neural Fields
by: Chen, Chuhan, et al.
Published: (2026)

mRadNet: A Compact Radar Object Detector with MetaFormer
by: Chen, Huaiyu, et al.
Published: (2025)

Test-Time Certifiable Self-Supervision to Bridge the Sim2Real Gap in Event-Based Satellite Pose Estimation
by: Jawaid, Mohsi, et al.
Published: (2024)

DPGLA: Bridging the Gap between Synthetic and Real Data for Unsupervised Domain Adaptation in 3D LiDAR Semantic Segmentation
by: Li, Wanmeng, et al.
Published: (2025)

Towards Sim-to-Real Industrial Parts Classification with Synthetic Dataset
by: Zhu, Xiaomeng, et al.
Published: (2024)

Close the Sim2real Gap via Physically-based Structured Light Synthetic Data Simulation
by: Bai, Kaixin, et al.
Published: (2024)

From Synthetic to Real: Toward Identity-Consistent Makeup Transfer with Synthetic and Real Data
by: Yu, Yue, et al.
Published: (2026)

Multi-clue Consistency Learning to Bridge Gaps Between General and Oriented Object in Semi-supervised Detection
by: Wang, Chenxu, et al.
Published: (2024)

IntrinsicReal: Adapting IntrinsicAnything from Synthetic to Real Objects
by: Wei, Xiaokang, et al.
Published: (2025)

BlendCLIP: Bridging Synthetic and Real Domains for Zero-Shot 3D Object Classification with Multimodal Pretraining
by: Khoche, Ajinkya, et al.
Published: (2025)

SynthDrive: Scalable Real2Sim2Real Sensor Simulation Pipeline for High-Fidelity Asset Generation and Driving Data Synthesis
by: Chen, Zhengqing, et al.
Published: (2025)

RoboGSim: A Real2Sim2Real Robotic Gaussian Splatting Simulator
by: Li, Xinhai, et al.
Published: (2024)

RadarGaussianDet3D: Gaussian Representation-based Real-time 3D Object Detection with 4D Automotive Radars
by: Xiong, Weiyi, et al.
Published: (2025)

SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images
by: Dhakal, Aayush, et al.
Published: (2026)

ComSim: Building Scalable Real-World Robot Data Generation via Compositional Simulation
by: Qin, Yiran, et al.
Published: (2026)

Mind the Domain Gap: Measuring the Domain Gap Between Real-World and Synthetic Point Clouds for Automated Driving Development
by: Duc, Nguyen, et al.
Published: (2025)