Panoptic-FlashOcc: An Efficient Baseline to Marry Semantic Occupancy with Panoptic via Instance Center
Zichen Yu, Changyong Shu, Qianpu Sun, Yifan Bian, Xiaobao Wei,, Jiangyong Yu, Zongdai Liu, Dawei Yang, Hui Li, Yan Chen

TL;DR
Panoptic-FlashOcc introduces a fast, efficient 2D framework for panoptic occupancy prediction that combines semantic and instance information, outperforming existing methods in speed and accuracy.
Contribution
It presents a lightweight, unified approach for real-time panoptic occupancy prediction, reducing memory and computation compared to voxel-based methods.
Findings
Achieves 38.5 RayIoU and 29.1 mIoU on Occ3D-nuScenes
Operates at 43.9 FPS for semantic occupancy
Scores 16.0 RayPQ for panoptic occupancy
Abstract
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 solutions for panoptic occupancy. In this paper, we propose Panoptic-FlashOcc, a straightforward yet robust 2D feature framework that enables realtime panoptic occupancy. Building upon the lightweight design of FlashOcc, our approach simultaneously learns semantic occupancy and class-aware instance clustering in a single network, these outputs are jointly incorporated through panoptic occupancy procession for panoptic occupancy. This approach effectively addresses the drawbacks of high memory and computation requirements associated with three-dimensional voxel-level representations. With its straightforward and efficient design that facilitates easy deployment, Panoptic-FlashOcc demonstrates remarkable…
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Taxonomy
TopicsSemantic Web and Ontologies
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
