ConFusion reaches 59.1 mAP and 65.6 NDS on nuScenes validation by combining heterogeneous queries with QMix cross-attention and QSwap feature exchange.
EA-LSS: Edge-aware Lift-splat-shot Framework for 3D BEV Object Detection
6 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 6representative citing papers
HGC-Det applies hyperbolic geometry to constrain cross-modal distillation between images and point clouds, with added semantic-guided voxel optimization and feature aggregation, yielding improved accuracy-efficiency trade-offs on SUN RGB-D, ARKitScenes, KITTI, and nuScenes.
DualViewMapDet fuses prior-traversal point cloud maps into camera features via dual perspective-view and bird's-eye-view encoding to improve 3D detection and tracking without LiDAR.
FusionSense uses server-side fusion learning, filter-out-safe labels, and edge compaction to enable runtime-adaptive multimodal sensing that cuts energy up to 33x while preserving task quality on RGB+Depth data.
REFNet++ aligns raw camera images and radar range-Doppler data into a shared bird's-eye polar view using variational encoders for multi-task vehicle detection and free space segmentation on the RADIal dataset.
A survey synthesizing sensor fusion strategies, AV datasets, and emerging LLM/VLM-powered object detection pipelines for autonomous vehicles.
citing papers explorer
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Control Your Queries: Heterogeneous Query Interaction for Camera-Radar Fusion
ConFusion reaches 59.1 mAP and 65.6 NDS on nuScenes validation by combining heterogeneous queries with QMix cross-attention and QSwap feature exchange.
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Hyperbolic Distillation: Geometry-Guided Cross-Modal Transfer for Robust 3D Object Detection
HGC-Det applies hyperbolic geometry to constrain cross-modal distillation between images and point clouds, with added semantic-guided voxel optimization and feature aggregation, yielding improved accuracy-efficiency trade-offs on SUN RGB-D, ARKitScenes, KITTI, and nuScenes.
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Leveraging Previous-Traversal Point Cloud Map Priors for Camera-Based 3D Object Detection and Tracking
DualViewMapDet fuses prior-traversal point cloud maps into camera features via dual perspective-view and bird's-eye-view encoding to improve 3D detection and tracking without LiDAR.
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FusionSense: Tri-Stage Near-Sensor Learning for Runtime-Adaptive Multimodal Edge Intelligence
FusionSense uses server-side fusion learning, filter-out-safe labels, and edge compaction to enable runtime-adaptive multimodal sensing that cuts energy up to 33x while preserving task quality on RGB+Depth data.
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REFNet++: Multi-Task Efficient Fusion of Camera and Radar Sensor Data in Bird's-Eye Polar View
REFNet++ aligns raw camera images and radar range-Doppler data into a shared bird's-eye polar view using variational encoders for multi-task vehicle detection and free space segmentation on the RADIal dataset.
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All You Need for Object Detection: From Pixels, Points, and Prompts to Next-Gen Fusion and Multimodal LLMs/VLMs in Autonomous Vehicles
A survey synthesizing sensor fusion strategies, AV datasets, and emerging LLM/VLM-powered object detection pipelines for autonomous vehicles.