Learning distilled collaboration graph for multi-agent perception
To promote better performance-bandwidth trade-off for multi-agent perception, we propose a
novel distilled collaboration graph (DiscoGraph) to model trainable, pose-aware, and …
novel distilled collaboration graph (DiscoGraph) to model trainable, pose-aware, and …
Where2comm: Communication-efficient collaborative perception via spatial confidence maps
Multi-agent collaborative perception could significantly upgrade the perception performance
by enabling agents to share complementary information with each other through …
by enabling agents to share complementary information with each other through …
Bridging the domain gap for multi-agent perception
Existing multi-agent perception algorithms usually select to share deep neural features
extracted from raw sensing data between agents, achieving a trade-off between accuracy …
extracted from raw sensing data between agents, achieving a trade-off between accuracy …
Core: Cooperative reconstruction for multi-agent perception
This paper presents CORE, a conceptually simple, effective and communication-efficient
model for multi-agent cooperative perception. It addresses the task from a novel perspective …
model for multi-agent cooperative perception. It addresses the task from a novel perspective …
Complementarity-enhanced and redundancy-minimized collaboration network for multi-agent perception
Multi-agent collaborative perception depends on sharing sensory information to improve
perception accuracy and robustness, as well as to extend coverage. The cooperative shared …
perception accuracy and robustness, as well as to extend coverage. The cooperative shared …
Spatio-temporal domain awareness for multi-agent collaborative perception
Multi-agent collaborative perception as a potential application for vehicle-to-everything
communication could significantly improve the perception performance of autonomous …
communication could significantly improve the perception performance of autonomous …
Distillbev: Boosting multi-camera 3d object detection with cross-modal knowledge distillation
Abstract 3D perception based on the representations learned from multi-camera bird's-eye-
view (BEV) is trending as cameras are cost-effective for mass production in autonomous …
view (BEV) is trending as cameras are cost-effective for mass production in autonomous …
X3kd: Knowledge distillation across modalities, tasks and stages for multi-camera 3d object detection
Recent advances in 3D object detection (3DOD) have obtained remarkably strong results for
LiDAR-based models. In contrast, surround-view 3DOD models based on multiple camera …
LiDAR-based models. In contrast, surround-view 3DOD models based on multiple camera …
Sparsefusion: Fusing multi-modal sparse representations for multi-sensor 3d object detection
By identifying four important components of existing LiDAR-camera 3D object detection
methods (LiDAR and camera candidates, transformation, and fusion outputs), we observe …
methods (LiDAR and camera candidates, transformation, and fusion outputs), we observe …
Bevdet4d: Exploit temporal cues in multi-camera 3d object detection
J Huang, G Huang - arXiv preprint arXiv:2203.17054, 2022 - arxiv.org
Single frame data contains finite information which limits the performance of the existing
vision-based multi-camera 3D object detection paradigms. For fundamentally pushing the …
vision-based multi-camera 3D object detection paradigms. For fundamentally pushing the …