Radar-Modulated Selection perturbs only the step size Δ and readout C parameters inside Mamba's selective scan with radar data while keeping other components image-only, yielding state-of-the-art depth estimation on nuScenes with up to 34% MAE reduction.
4d millimeter-wave radar in autonomous driving: A survey.arXiv preprint arXiv:2306.04242
5 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 5representative citing papers
RAVEN introduces a chirp-wise streaming radar perception network with MIMO-preserving encoders, learnable cross-antenna mixing, and early-exit to deliver competitive detection and BEV segmentation at reduced compute and latency.
AttenNKF augments InEKF with an attention-based neural compensator trained in latent space to correct foot-slip errors in legged robot state estimation.
POLAR converts scaleless monocular depth maps to metric scale via radar-guided polynomial fitting and first-derivative regularization, claiming 24.9% MAE and 33.2% RMSE gains over prior methods on three datasets.
PULSE stabilizes mmWave human pose estimation by screening Doppler motion prompts before injecting them into spatial magnitude reasoning.
citing papers explorer
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Selection, Not Fusion: Radar-Modulated State Space Models for Radar-Camera Depth Estimation
Radar-Modulated Selection perturbs only the step size Δ and readout C parameters inside Mamba's selective scan with radar data while keeping other components image-only, yielding state-of-the-art depth estimation on nuScenes with up to 34% MAE reduction.
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RAVEN: Radar Adaptive Vision Encoders for Efficient Chirp-wise Object Detection and Segmentation
RAVEN introduces a chirp-wise streaming radar perception network with MIMO-preserving encoders, learnable cross-antenna mixing, and early-exit to deliver competitive detection and BEV segmentation at reduced compute and latency.
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Attention-Based Neural-Augmented Kalman Filter for Legged Robot State Estimation
AttenNKF augments InEKF with an attention-based neural compensator trained in latent space to correct foot-slip errors in legged robot state estimation.
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Radar-Guided Polynomial Fitting for Metric Depth Estimation
POLAR converts scaleless monocular depth maps to metric scale via radar-guided polynomial fitting and first-derivative regularization, claiming 24.9% MAE and 33.2% RMSE gains over prior methods on three datasets.
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Doppler Prompting for Stable mmWave-based Human Pose Estimation
PULSE stabilizes mmWave human pose estimation by screening Doppler motion prompts before injecting them into spatial magnitude reasoning.