6 papers
FQ-PETR: Fully Quantized Position Embedding Transformation for Multi-View 3D Object Detection
Jiangyong Yu, Changyong Shu, Sifan Zhou +4
Camera-based multi-view 3D detection is crucial for autonomous driving. PETR and its variants (PETRs) excel in benchmarks but face deployment challenges due to high computational c…
FQ-PETR: Fully Quantized Position Embedding Transformation for Multi-View 3D Object Detection
Jiangyong Yu, Changyong Shu, Sifan Zhou +4
Camera-based multi-view 3D detection is crucial for autonomous driving. PETR and its variants (PETRs) excel in benchmarks but face deployment challenges due to high computational c…
MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization
JiangYong Yu, Sifan Zhou, Dawei Yang +7
Multimodal large language models (MLLMs) have garnered widespread attention due to their ability to understand multimodal input. However, their large parameter sizes and substantia…
GSRender: Deduplicated Occupancy Prediction via Weakly Supervised 3D Gaussian Splatting
Qianpu Sun, Changyong Shu, Sifan Zhou +6
Weakly-supervised 3D occupancy perception is crucial for vision-based autonomous driving in outdoor environments. Previous methods based on NeRF often face a challenge in balancing…
UltimateDO: An Efficient Framework to Marry Occupancy Prediction with 3D Object Detection via Channel2height
Zichen Yu, Changyong Shu
Occupancy and 3D object detection are characterized as two standard tasks in modern autonomous driving system. In order to deploy them on a series of edge chips with better precisi…
Panoptic-FlashOcc: An Efficient Baseline to Marry Semantic Occupancy with Panoptic via Instance Center
Zichen Yu, Changyong Shu, Qianpu Sun +7
Panoptic occupancy poses a novel challenge by aiming to integrate instance occupancy and semantic occupancy within a unified framework. However, there is still a lack of efficient…