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Paper Citation Record · LEDGER

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception

As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.17351.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.17351 v1

Coverage vector

measured 41 of 41 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-01T18:18:42.064125Z

measured 41 of 41 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

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measured 0 of 1 external citation measurements

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41 of 41 outbound references displayed

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Outbound references

Observation 1e488f1c-0ee8-48fa-88f4-340c9c018d2f · outbound

This paper cites Deepfusion: A robust and modular 3d object detector for lidars, cam- eras and radars,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Deepfusion: A robust and modular 3d object detector for lidars, cam- eras and radars,

Reference 1

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Observation 6893c132-11cb-4862-81e3-cc5801b662d1 · outbound

This paper cites Experimental validation of lidar sensors used in vehicular applications by using a mobile platform for distance and speed measurements,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Experimental validation of lidar sensors used in vehicular applications by using a mobile platform for distance and speed measurements,

Reference 2

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Observation 88cc0ca3-5b3f-49b2-9dd7-dd10c74f3600 · outbound

This paper cites An overview of autonomous vehicles sensors and their vulnerability to weather conditions,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception An overview of autonomous vehicles sensors and their vulnerability to weather conditions,

Reference 3

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Observation 715177a9-2e25-4626-b65d-06cab4f4c257 · outbound

This paper cites Mimo radar: an idea whose time has come,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Mimo radar: an idea whose time has come,

Reference 4

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Observation da4213f3-df95-4615-9327-c80951a08f89 · outbound

This paper cites Richards,Fundamentals of Radar Signal Processing, Second Edition.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Richards,Fundamentals of Radar Signal Processing, Second Edition

Reference 5

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Observation 8b4e8476-6f79-41aa-b692-768f3199a195 · outbound

This paper cites Compressed sensing,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Compressed sensing,

Reference 6

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Observation 1a5c7b5e-f326-45e2-811a-54f3d76ca190 · outbound

This paper cites Mimo radar using compressive sampling,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Mimo radar using compressive sampling,

Reference 7

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Observation 4458bc03-abd9-4176-8c2c-21fbcdb52fba · outbound

This paper cites Spatial compressive sensing for mimo radar,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Spatial compressive sensing for mimo radar,

Reference 8

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Observation d6d117a4-b89f-4d73-b825-db00f8f7cdf4 · outbound

This paper cites Joint optimization of system design and reconstruction in MIMO radar imaging.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Joint optimization of system design and reconstruction in MIMO radar imaging

Reference 9

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Observation 9cc38542-7123-4001-87b4-4a237cab1c37 · outbound

This paper cites A review of multi-sensor fusion in autonomous driving,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception A review of multi-sensor fusion in autonomous driving,

Reference 10

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Observation 47c43bd6-83a7-43dc-b4bc-efb82e56a9c6 · outbound

This paper cites BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

Reference 11

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Observation a41deb45-a5dd-48d7-bf20-dcadd9092e6e · outbound

This paper cites Metabev: Solving sensor failures for bev detection and map segmentation,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Metabev: Solving sensor failures for bev detection and map segmentation,

Reference 12

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Observation c5f3620a-9ccd-487c-b2ac-a951d89f0350 · outbound

This paper cites Centerfusion: Center-based radar and camera fusion for 3d object detection,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Centerfusion: Center-based radar and camera fusion for 3d object detection,

Reference 13

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Observation 2339f7be-d2b8-44ea-a1de-47f16f695ce2 · outbound

This paper cites RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection Systems.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection Systems

Reference 14

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Observation 280bdf7a-0a69-4873-9ec6-20b024b3de50 · outbound

This paper cites Bev-guided multi-modality fusion for driving perception,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Bev-guided multi-modality fusion for driving perception,

Reference 15

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Observation 3267065a-c108-4273-9c86-6f3508222ea8 · outbound

This paper cites Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion,

Reference 16

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Observation 2181e978-f1b8-48c4-8e5d-d93e5d5b0cfd · outbound

This paper cites Raw High-Definition Radar for Multi-Task Learning.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Raw High-Definition Radar for Multi-Task Learning

Reference 17

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Observation fbd95151-9d5c-40a2-ae13-806a58446bdf · outbound

This paper cites Pointpillars: Fast encoders for object detection from point clouds,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Pointpillars: Fast encoders for object detection from point clouds,

Reference 18

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Observation aaaccb42-1783-4980-813a-2c2eea95cbce · outbound

This paper cites Multi-class road user detection with 3+1d radar in the view-of-delft dataset,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Multi-class road user detection with 3+1d radar in the view-of-delft dataset,

Reference 19

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Observation a1ec8810-f54d-4598-b89a-5b31f9c5bb54 · outbound

This paper cites RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud

Reference 20

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Observation 7b459242-1588-47d0-aa5e-9da095577f30 · outbound

This paper cites Semrafiner: Panoptic segmentation in sparse and noisy radar point clouds,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Semrafiner: Panoptic segmentation in sparse and noisy radar point clouds,

Reference 21

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Observation a0e9b37f-03c7-4fac-85a5-cf5a92baebee · outbound

This paper cites T-fftradnet: Object detection with swin vision transformers from raw adc radar signals,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception T-fftradnet: Object detection with swin vision transformers from raw adc radar signals,

Reference 22

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Observation 3e6a3678-aa33-41f6-89ff-a365478583c5 · outbound

This paper cites ADCNet: Learning from Raw Radar Data via Distillation.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception ADCNet: Learning from Raw Radar Data via Distillation

Reference 23

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Observation cccaedc5-cc31-4701-9ab0-0b830611086f · outbound

This paper cites Categorical reparameterization with gumbel-softmax,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Categorical reparameterization with gumbel-softmax,

Reference 24

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Observation b0e86431-9f80-4d9d-b498-2d78914941f7 · outbound

This paper cites U-Net: Convolutional Networks for Biomedical Image Segmentation.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception U-Net: Convolutional Networks for Biomedical Image Segmentation

Reference 25

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Observation 2ed77c3c-9de3-4c7b-b447-7f41bce4f437 · outbound

This paper cites Joint optimization of sparse MIMO arrays and imaging methods,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Joint optimization of sparse MIMO arrays and imaging methods,

Reference 26

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Observation 46853d5b-f54d-4f7d-81e2-50e528fa6931 · outbound

This paper cites Grif-net: Gated region of interest fusion network for robust 3d object detection from radar point cloud and monocular image,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Grif-net: Gated region of interest fusion network for robust 3d object detection from radar point cloud and monocular image,

Reference 27

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Observation 3865b404-204c-4e8d-8a93-df4b12f159d7 · outbound

This paper cites Interfusion: Interaction-based 4d radar and lidar fusion for 3d object detection,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Interfusion: Interaction-based 4d radar and lidar fusion for 3d object detection,

Reference 28

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Observation 74765481-2985-4462-8cbe-7d94fe19e211 · outbound

This paper cites Towards robust 3d object detection with lidar and 4d radar fusion in various weather conditions,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Towards robust 3d object detection with lidar and 4d radar fusion in various weather conditions,

Reference 29

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Observation aeb71d0d-d77f-4ca3-9f85-16e02d37ac66 · outbound

This paper cites Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Delving into the Devils of Bird's-eye-view Perception: A Review, Evaluation and Recipe

Reference 30

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Observation 3ca2d37a-f6b5-472f-93e9-350de2a0db98 · outbound

This paper cites Exploring mmwave radar and camera fusion for high-resolution and long-range depth imaging,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Exploring mmwave radar and camera fusion for high-resolution and long-range depth imaging,

Reference 31

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Observation 480feb6d-78e4-43ca-91ea-f16edbe2b3ec · outbound

This paper cites Relaxed multivariate bernoulli distribution and its applications to deep generative models,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Relaxed multivariate bernoulli distribution and its applications to deep generative models,

Reference 32

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Observation c7383a56-4a79-451a-bf5b-81cf390a8cdf · outbound

This paper cites Reparameterizable Subset Sampling via Continuous Relaxations.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Reparameterizable Subset Sampling via Continuous Relaxations

Reference 33

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Observation 69c2f697-3962-48e3-8090-9e8b4aa27921 · outbound

This paper cites Feature Pyramid Networks for Object Detection.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Feature Pyramid Networks for Object Detection

Reference 34

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Observation 174aad2e-40b0-474f-9ac7-9b9efb8bae72 · outbound

This paper cites Polarformer: Multi-camera 3d object detection with polar transformer,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Polarformer: Multi-camera 3d object detection with polar transformer,

Reference 35

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Observation c9c9fcdc-6683-4963-8db6-fa43d3e5e3bd · outbound

This paper cites Radarsimx: The tool chain for radar simulation,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Radarsimx: The tool chain for radar simulation,

Reference 36

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source=pdf_text observed=2026-08-01T18:18:41.789197Z digest=sha256:23c25ab7f0168690f1938575fdbe7804e796b309c77bfc8d8fee6548a29b409d

Observation e017fa88-9ebf-4e36-a929-1094f85a9dab · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception ShapeNet: An Information-Rich 3D Model Repository

Reference 37

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no resolver link, observed 2026-08-01T18:18:41.862649Z

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source=pdf_text observed=2026-08-01T18:18:41.862649Z digest=sha256:b7a0e48b35df4503b9465bd4686672061ea11328934334a1f775b6e6e9340040

Observation 5b151414-409e-4a61-a0ae-4b86fd62a292 · outbound

This paper cites Adam: A method for stochastic optimization,.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Adam: A method for stochastic optimization,

Reference 38

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no resolver link, observed 2026-08-01T18:18:41.940688Z

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source=pdf_text observed=2026-08-01T18:18:41.940688Z digest=sha256:2cfaed0f1d309f504f52f81f7c71790fe3b912921a1cefa66aa250326e7daf03

Observation f77423fb-6dda-4bbb-8b6b-0ad459f674e1 · outbound

This paper cites Dick and F.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception Dick and F

Reference 39

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no resolver link, observed 2026-08-01T18:18:42.064125Z

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source=pdf_text observed=2026-08-01T18:18:42.064125Z digest=sha256:7b468e70cbdd9940bb273429bd130d5512e8b810170837bb686f5db9f78e9744

Observation 5514f2cd-d6bd-4790-8965-effb26bba9ed · outbound

This paper cites PointPillars: Fast Encoders for Object Detection from Point Clouds.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception PointPillars: Fast Encoders for Object Detection from Point Clouds

Reference 2019

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no resolver link, observed 2026-08-01T18:18:39.994331Z

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source=pdf_text observed=2026-08-01T18:18:39.994331Z digest=sha256:44ceceb679ab758990d08d4a47a229300748d79fbeedc21b763983a031f09256

Observation 98ce1aa0-2051-4b6e-92c0-7e56470dfc27 · outbound

This paper cites T-FFTRadNet: Object Detection with Swin Vision Transformers from Raw ADC Radar Signals.

DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception T-FFTRadNet: Object Detection with Swin Vision Transformers from Raw ADC Radar Signals

Reference 2023

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no resolver link, observed 2026-08-01T18:18:40.432037Z

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source=pdf_text observed=2026-08-01T18:18:40.432037Z digest=sha256:42764f2fce9de40627d6093af40a9c4726bb6db59acdaa55581d3cd211d5189e

Pith citing papers

No inbound Pith citation observations are available.