Papers 3D Panoptic Segmentation
“3D Panoptic Segmentation” 태그가 달린 논문 15편 · 필터 해제
How Do Images Align and Complement LiDAR? Towards a Harmonized Multi-modal 3D Panoptic Segmentation
LiDAR-based 3D panoptic segmentation often struggles with the inherent sparsity of data from LiDAR sensors, which makes it challenging to accurately recognize distant or small objects. Recently, a few studies have sought…
3D Panoptic SegmentationData AugmentationDecoderPanoptic Segmentation+13D Hierarchical Panoptic Segmentation in Real Orchard Environments Across Different Sensors
Crop yield estimation is a relevant problem in agriculture, because an accurate yield estimate can support farmers' decisions on harvesting or precision intervention. Robots can help to automate this process. To do so, t…
3D Panoptic SegmentationInstance SegmentationPanoptic SegmentationSegmentation+1PCF-Lift: Panoptic Lifting by Probabilistic Contrastive Fusion
Panoptic lifting is an effective technique to address the 3D panoptic segmentation task by unprojecting 2D panoptic segmentations from multi-views to 3D scene. However, the quality of its results largely depends on the 2…
3D Panoptic SegmentationPanoptic SegmentationSegmentationPanopticRecon: Leverage Open-vocabulary Instance Segmentation for Zero-shot Panoptic Reconstruction
Panoptic reconstruction is a challenging task in 3D scene understanding. However, most existing methods heavily rely on pre-trained semantic segmentation models and known 3D object bounding boxes for 3D panoptic segmenta…
3D Panoptic SegmentationInstance SegmentationPanoptic SegmentationScene Understanding+3Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering
We introduce a highly efficient method for panoptic segmentation of large 3D point clouds by redefining this task as a scalable graph clustering problem. This approach can be trained using only local auxiliary tasks, the…
3D Panoptic Segmentation3D Semantic SegmentationGraph ClusteringPanoptic Segmentation+23D Open-Vocabulary Panoptic Segmentation with 2D-3D Vision-Language Distillation
3D panoptic segmentation is a challenging perception task, especially in autonomous driving. It aims to predict both semantic and instance annotations for 3D points in a scene. Although prior 3D panoptic segmentation app…
3D Panoptic SegmentationAutonomous DrivingClassificationOpen Vocabulary Panoptic Segmentation+2PanoRecon: Real-Time Panoptic 3D Reconstruction from Monocular Video
We introduce the Panoptic 3D Reconstruction task a unified and holistic scene understanding task for a monocular video. And we present PanoRecon - a novel framework to address this new task which realizes an online g…
3D Panoptic Segmentation3D ReconstructionPanoptic SegmentationScene UnderstandingPanopticNDT: Efficient and Robust Panoptic Mapping
As the application scenarios of mobile robots are getting more complex and challenging, scene understanding becomes increasingly crucial. A mobile robot that is supposed to operate autonomously in indoor environments mus…
2D Panoptic Segmentation3D Panoptic Segmentation3D Semantic SegmentationPanoptic Segmentation+4Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR Sequences
Scene understanding is crucial for autonomous systems to reliably navigate in the real world. Panoptic segmentation of 3D LiDAR scans allows us to semantically describe a vehicle’s environment by predicting semantic clas…
3D Panoptic Segmentation4D Panoptic SegmentationNavigatePanoptic Segmentation+2LiDAR-Camera Panoptic Segmentation via Geometry-Consistent and Semantic-Aware Alignment
3D panoptic segmentation is a challenging perception task that requires both semantic segmentation and instance segmentation. In this task, we notice that images could provide rich texture, color, and discriminative info…
3D Panoptic SegmentationInstance SegmentationPanoptic SegmentationSegmentation+1PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentation
Comprehensive modeling of the surrounding 3D world is key to the success of autonomous driving. However, existing perception tasks like object detection, road structure segmentation, depth & elevation estimation, and ope…
3D Panoptic SegmentationAutonomous Drivingobject-detectionObject Detection+5BUOL: A Bottom-Up Framework with Occupancy-aware Lifting for Panoptic 3D Scene Reconstruction From A Single Image
Understanding and modeling the 3D scene from a single image is a practical problem. A recent advance proposes a panoptic 3D scene reconstruction task that performs both 3D reconstruction and 3D panoptic segmentation from…
3D Panoptic Segmentation3D Reconstruction3D Scene ReconstructionPanoptic SegmentationSAD: Segment Any RGBD
The Segment Anything Model (SAM) has demonstrated its effectiveness in segmenting any part of 2D RGB images. However, SAM exhibits a stronger emphasis on texture information while paying less attention to geometry inform…
3D Panoptic SegmentationOpen Vocabulary Semantic SegmentationOpen-Vocabulary Semantic SegmentationPanoptic Segmentation+2Nerflets: Local Radiance Fields for Efficient Structure-Aware 3D Scene Representation from 2D Supervision
We address efficient and structure-aware 3D scene representation from images. Nerflets are our key contribution -- a set of local neural radiance fields that together represent a scene. Each nerflet maintains its own spa…
3D Panoptic SegmentationPanoptic SegmentationPositionA Versatile Multi-View Framework for LiDAR-based 3D Object Detection with Guidance from Panoptic Segmentation
3D object detection using LiDAR data is an indispensable component for autonomous driving systems. Yet, only a few LiDAR-based 3D object detection methods leverage segmentation information to further guide the detection …
3D Object Detection3D Panoptic SegmentationAutonomous DrivingObject+4