Panoptic Segmentation

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Overview

Panoptic segmentation combines semantic segmentation of background-like regions (“stuff”) with instance segmentation of countable objects (“things”), giving a unified account of a scene. Common approaches use query-based transformer decoders, unified-kernel models, and temporal or geometric association, with extensions to open-vocabulary recognition, 3D point clouds, video, and multi-view scenes. Methods are commonly evaluated with Panoptic Quality on benchmarks such as COCO, Cityscapes, and ScanNet, while video and driving settings also test temporal consistency and robustness to adverse conditions. A central challenge is maintaining accurate, consistent instance identities while recognizing unfamiliar objects and meeting the efficiency and annotation constraints of real-world deployment.

Latest papers

CardsList

38 papers7 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

  1. LiPS: Lightweight Panoptic Segmentation for Resource-Constrained Robotics

    Apr 1, 2026Calvin Galagain, Martyna Poreba, François Goulette +1Panoptic SegmentationRobotic Perception

    Université Paris-Saclay, CEA LIST, F-91120 Palaiseau, France · U2IS, ENSTA, Institut Polytechnique de Paris, 91120 Palaiseau, France · University of Bonn, Center for Robotics, Bonn, Germany

  2. Mitigating Objectness Bias and Region-to-Text Misalignment for Open-Vocabulary Panoptic Segmentation

    Mar 22, 2026Nikolay Kormushev, Josip Šarić, Matej KristanPanoptic SegmentationVision-Language Alignment

    University of Ljubljana Faculty of Comp. and Inf. Science · ETH Zurich Dept. of Computer Science · University of Zagreb Faculty of Elec. Eng. and Computing

  3. PanORama: Multiview Consistent Panoptic Segmentation in Operating Rooms

    Mar 20, 2026Tuna Gürbüz, Ege Özsoy, Tony Danjun Wang +1Panoptic SegmentationMulti-View Consistency

    Computer Aided Medical Procedures, Technische Universität München, Germany · MCML, Germany

  4. OnlinePG: Online Open-Vocabulary Panoptic Mapping with 3D Gaussian Splatting

    Mar 19, 2026Hongjia Zhai, Qi Zhang, Xiaokun Pan +53D Scene UnderstandingPanoptic Segmentation

    State Key Lab of CAD & CG, Zhejiang University · VIVO BlueImage Lab · HKUST

  5. Efficient RGB-D Scene Understanding via Multi-task Adaptive Learning and Cross-dimensional Feature Guidance

    Mar 8, 2026Guodong Sun, Junjie Liu, Gaoyang Zhang +23D Scene UnderstandingSemantic Segmentation

    School of Mechanical Engineering, Hubei University of Technology, Wuhan, 430068, China · Hubei Key Laboratory of Modern Manufacturing Quality Engineering, Hubei University of Technology, Wuhan, 430068, China · Vehicle Measurement, Control and Safety Key Laboratory of Sichuan Province, Xihua University, Chengdu, 610039, China +2

  6. UP-Fuse: Uncertainty-guided LiDAR-Camera Fusion for 3D Panoptic Segmentation

    Feb 22, 2026Rohit Mohan, Florian Drews, Yakov Miron +2Camera-LiDAR FusionPanoptic Segmentation

    University of Freiburg, Germany · Robert Bosch GmbH, Germany · University of Haifa

  7. Training-Free Global Geometric Association for 4D LiDAR Panoptic Segmentation

    Dec 22, 2025Gyeongrok Oh, Youngdong Jang, Jonghyun Choi +3Panoptic Segmentation3D Instance Segmentation

    Korea University · Hyundai Motor Company · Sogang University +1

  8. Open-World Panoptic Segmentation

    Dec 17, 2024Matteo Sodano, Federico Magistri, Jens Behley +1Image SegmentationPanoptic Segmentation

    Center for Robotics, University of Bonn, Germany, and the Lamarr Institute for Machine Learning and Artificial Intelligence, Germany