Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:19:48.261004Z
Paper Citation Record · LEDGER
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection
As of 19 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2505.07398.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
54 of 54 outbound references displayed
- verified exact0
- verified fuzzy48
- unresolved6
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b05d3ff9-d955-4df5-9c91-dce2202c60c0 · outbound
This paper cites nuscenes: A multimodal dataset for autonomous driving.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection nuscenes: A multimodal dataset for autonomous driving
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.150177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 82065627-bd66-4f9e-90b9-3d06bf93acb7 · outbound
This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Are we ready for autonomous driving? the kitti vision benchmark suite
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.133304Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b1cf7701-ae84-479d-82e3-e127a72f9247 · outbound
This paper cites Benchmarking robustness of 3d object detection to common corruptions.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Benchmarking robustness of 3d object detection to common corruptions
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.117738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 62ca6c5b-afe3-47ac-929b-30b46ec907b4 · outbound
This paper cites Pointrcnn: 3d object proposal generation and detection from point cloud.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Pointrcnn: 3d object proposal generation and detection from point cloud
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.102281Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8e02146b-81b3-40fb-9c9d-ea259901438c · outbound
This paper cites V oxelnet: End-to-end learning for point cloud based 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection V oxelnet: End-to-end learning for point cloud based 3d object detection
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.086365Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1fc66151-b713-4a71-9f3f-89bc5c2b2542 · outbound
This paper cites Sp-det: Leveraging saliency prediction for voxel-based 3d object detection in sparse point cloud.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Sp-det: Leveraging saliency prediction for voxel-based 3d object detection in sparse point cloud
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.070421Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2bb1b0f3-79cc-4848-929d-c6e0b1eeb7c8 · outbound
This paper cites Pv-rcnn: Point-voxel feature set abstraction for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Pv-rcnn: Point-voxel feature set abstraction for 3d object detection
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.054139Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cb559a0e-0e7e-4052-b8ff-099ece69e29a · outbound
This paper cites Fcos3d: Fully convolutional one-stage monocular 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Fcos3d: Fully convolutional one-stage monocular 3d object detection
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.037473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ead53044-3fc7-43c4-ab9a-5998e4496d80 · outbound
This paper cites BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:19:48.030816Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 88ee2a53-8af7-485d-a89c-0bd250d0c7eb · outbound
This paper cites Pointpainting: Sequential fusion for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Pointpainting: Sequential fusion for 3d object detection
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.022008Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ba348782-a29c-467f-8b79-408ad0da5a42 · outbound
This paper cites Pointaug- menting: Cross-modal augmentation for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Pointaug- menting: Cross-modal augmentation for 3d object detection
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:49.006836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0ca4b8b8-2ca1-48b7-9482-02f7ac86b9fb · outbound
This paper cites Virtual sparse convolution for multimodal 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Virtual sparse convolution for multimodal 3d object detection
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.990662Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e975e11e-d685-45cd-8f17-458f90879292 · outbound
This paper cites Virpnet: A multimodal virtual point generation network for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Virpnet: A multimodal virtual point generation network for 3d object detection
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.974100Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c8f5edd1-00e1-47b8-acc7-fedc298c329e · outbound
This paper cites Transfusion: Robust lidar-camera fusion for 3d object detection with transformers.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Transfusion: Robust lidar-camera fusion for 3d object detection with transformers
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.957996Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 13663ff6-e068-45a8-b4a2-5bf811957b20 · outbound
This paper cites Vpfnet: Improving 3d object detection with virtual point based lidar and stereo data fusion.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Vpfnet: Improving 3d object detection with virtual point based lidar and stereo data fusion
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.942801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d571a4f0-7f27-4e7c-a9a1-8fb953084132 · outbound
This paper cites Futr3d: A unified sensor fusion framework for 3d detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Futr3d: A unified sensor fusion framework for 3d detection
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.926631Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 35a05d87-b610-497a-862b-fee9e129aa17 · outbound
This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Deformable DETR: Deformable Transformers for End-to-End Object Detection
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:19:48.070453Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c768db45-6f4f-41f4-9ab8-08abc16c5682 · outbound
This paper cites 3d-dfm: Anchor-free multimodal 3-d object detection with dynamic fusion module for autonomous driving.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection 3d-dfm: Anchor-free multimodal 3-d object detection with dynamic fusion module for autonomous driving
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.910468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation eecef47a-a8a7-4bec-8672-387228bf4bfb · outbound
This paper cites Cl3d: Camera-lidar 3d object detection with point feature enhancement and point-guided fusion.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Cl3d: Camera-lidar 3d object detection with point feature enhancement and point-guided fusion
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.895022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6fe6de80-ef23-46ec-a924-38e99361dc17 · outbound
This paper cites Bevfusion: A simple and robust lidar-camera fusion framework.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Bevfusion: A simple and robust lidar-camera fusion framework
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.878724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 78d2932a-0947-4f7e-bf0a-535cde5714ab · outbound
This paper cites Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Bevfusion: Multi-task multi-sensor fusion with unified bird’s-eye view representation
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.862155Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cd6438c4-b74b-4275-9474-ff6b79dc9107 · outbound
This paper cites Sparsefusion: Fusing multi-modal sparse representations for multi- sensor 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Sparsefusion: Fusing multi-modal sparse representations for multi- sensor 3d object detection
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.844086Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1c8c5eb0-699d-43fa-b178-c691aefce972 · outbound
This paper cites Ob- jectfusion: Multi-modal 3d object detection with object-centric fusion.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Ob- jectfusion: Multi-modal 3d object detection with object-centric fusion
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.827323Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 744260db-4428-4266-aa76-366cdbe3eed4 · outbound
This paper cites Cross Modal Transformer: Towards Fast and Robust 3D Object Detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Cross Modal Transformer: Towards Fast and Robust 3D Object Detection
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:19:48.105741Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 97b01806-4d72-49a6-8c2f-3e6a6ccb77d3 · outbound
This paper cites Logonet: Towards accurate 3d object detection with local-to-global cross-modal fusion.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Logonet: Towards accurate 3d object detection with local-to-global cross-modal fusion
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.811355Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ced202ec-3bd2-4b36-bed5-ed4ab4a0daf4 · outbound
This paper cites Is-fusion: Instance-scene collaborative fusion for multimodal 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Is-fusion: Instance-scene collaborative fusion for multimodal 3d object detection
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.794551Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 9b99bf3b-fc75-4bfa-a9a3-aaa60ac9d136 · outbound
This paper cites Clocs: Camera-lidar object candidates fusion for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Clocs: Camera-lidar object candidates fusion for 3d object detection
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.778010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 9f9a4e19-90d3-42cb-b06c-ad8ad5e8bf85 · outbound
This paper cites Attention is all you need.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Attention is all you need
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:19:48.125768Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 499e393a-cfae-4d3c-b9a7-7f170c5a1cb3 · outbound
This paper cites V oxel r-cnn: Towards high performance voxel-based 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection V oxel r-cnn: Towards high performance voxel-based 3d object detection
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.752385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 07d810af-489d-4ba9-856e-19ee2905c4aa · outbound
This paper cites Mask r-cnn.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Mask r-cnn
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.736856Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 14589134-4160-4679-961b-d849ce31d796 · outbound
This paper cites MMDetection3D: OpenMMLab next- generation platform for general 3D object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection MMDetection3D: OpenMMLab next- generation platform for general 3D object detection
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.721445Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b3d2c6f3-4c5d-4052-abbd-c25a6db489e4 · outbound
This paper cites Second: Sparsely embedded convolutional detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Second: Sparsely embedded convolutional detection
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:19:48.145778Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 687d7712-84e3-4d96-aa77-b556dc3d213d · outbound
This paper cites Deep residual learning for image recognition.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Deep residual learning for image recognition
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.695094Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5b9aac97-735f-42b1-92d6-42a60563a49d · outbound
This paper cites A convnet for the 2020s.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection A convnet for the 2020s
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.678962Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 872201dd-0d8c-46b8-8010-2d245aab7013 · outbound
This paper cites Feature pyramid networks for object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Feature pyramid networks for object detection
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.662450Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d511a416-d6e3-4e42-b45f-9f554455f4e1 · outbound
This paper cites BEVPoolv2: A Cutting-edge Implementation of BEVDet Toward Deployment.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection BEVPoolv2: A Cutting-edge Implementation of BEVDet Toward Deployment
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:19:48.165460Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2d242a8f-938d-4333-8d48-b13044b5ca76 · outbound
This paper cites Deepinteraction: 3d object detection via modality interaction.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Deepinteraction: 3d object detection via modality interaction
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.646099Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 528055ad-109f-4f5a-ae15-a01d6b01c368 · outbound
This paper cites Msmdfusion: Fusing lidar and camera at multiple scales with multi-depth seeds for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Msmdfusion: Fusing lidar and camera at multiple scales with multi-depth seeds for 3d object detection
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.630869Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 610b4f64-2386-4413-a568-4ede8b3fc362 · outbound
This paper cites Focalformer3d: focusing on hard instance for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Focalformer3d: focusing on hard instance for 3d object detection
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.614777Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 9ae3c0ec-e981-4a12-b205-85c390be3432 · outbound
This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Swin transformer: Hierarchical vision transformer using shifted windows
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.599370Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 973cdd00-2d37-4a97-b3d4-f6b41251e6ee · outbound
This paper cites Gafusion: Adaptive fusing lidar and camera with multiple guidance for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Gafusion: Adaptive fusing lidar and camera with multiple guidance for 3d object detection
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.584025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 77c0ea22-678b-438a-bba2-6930a8af205a · outbound
This paper cites Deformable feature aggregation for dynamic multi- modal 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Deformable feature aggregation for dynamic multi- modal 3d object detection
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.568175Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cc418c53-1f8e-4e85-8091-84ba47194757 · outbound
This paper cites Cspnet: A new backbone that can enhance learning capability of cnn.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Cspnet: A new backbone that can enhance learning capability of cnn
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.551808Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ff888c21-7ee7-4fe1-befd-2cc09ff3e34c · outbound
This paper cites Unifying voxel-based representation with transformer for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Unifying voxel-based representation with transformer for 3d object detection
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.535914Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 489ac247-82a0-496d-a427-542b500c86bb · outbound
This paper cites An energy and gpu-computation efficient backbone network for real-time object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection An energy and gpu-computation efficient backbone network for real-time object detection
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.519919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 38ae17c9-e928-4d63-a10b-bc319b7089c4 · outbound
This paper cites Unitr: A unified and efficient multi- modal transformer for bird’s-eye-view representation.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Unitr: A unified and efficient multi- modal transformer for bird’s-eye-view representation
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.503545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6c6eea64-195d-49f7-8ea5-a18ddc53ac22 · outbound
This paper cites Dsvt: Dynamic sparse voxel transformer with rotated sets.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Dsvt: Dynamic sparse voxel transformer with rotated sets
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.487399Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation aafe7d2c-81f4-4a17-a68f-41b5df8f1e6b · outbound
This paper cites Unipad: A universal pre-training paradigm for autonomous driving.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Unipad: A universal pre-training paradigm for autonomous driving
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.471712Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 77e4e6c5-5457-4825-a8f6-d8190c79eaed · outbound
This paper cites Sparselif: High-performance sparse lidar-camera fusion for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Sparselif: High-performance sparse lidar-camera fusion for 3d object detection
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.454524Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 01024cfa-1dec-4488-a9da-aa126b17e058 · outbound
This paper cites Pointfusion: Deep sensor fusion for 3d bounding box estimation.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Pointfusion: Deep sensor fusion for 3d bounding box estimation
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.436455Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 13a9e774-d388-4a80-9653-7b60a01f2402 · outbound
This paper cites Epnet: Enhancing point features with image semantics for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Epnet: Enhancing point features with image semantics for 3d object detection
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.419324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 511b645c-e2bd-4c91-82c3-786db36f15e0 · outbound
This paper cites Cat-det: Contrastively aug- mented transformer for multi-modal 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Cat-det: Contrastively aug- mented transformer for multi-modal 3d object detection
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.403425Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 7b866a5a-94d2-4e3b-b888-bea534d10183 · outbound
This paper cites Focal sparse convolutional networks for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection Focal sparse convolutional networks for 3d object detection
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.386385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5ddd3669-909c-46b6-9e1a-62df4591a492 · outbound
This paper cites V oxel field fusion for 3d object detection.
DepthFusion: Depth-Aware Hybrid Feature Fusion for LiDAR-Camera 3D Object Detection V oxel field fusion for 3d object detection
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T22:19:48.368786Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Pith citing papers
No inbound Pith citation observations are available.