Papers 2D Panoptic Segmentation
“2D Panoptic Segmentation” 태그가 달린 논문 10편 · 필터 해제
XD-MAP: Cross-Modal Domain Adaptation via Semantic Parametric Maps for Scalable Training Data Generation
Until open-world foundation models match the performance of specialized approaches, deep learning systems remain dependent on task- and sensor-specific data availability. To bridge the gap between available datasets and …
2D Semantic Segmentation2D Panoptic Segmentation3D Semantic SegmentationDomain AdaptationPanSt3R: Multi-view Consistent Panoptic Segmentation
Panoptic segmentation of 3D scenes, involving the segmentation and classification of object instances in a dense 3D reconstruction of a scene, is a challenging problem, especially when relying solely on unposed 2D images…
2D Panoptic Segmentation3D geometry3DGS3D Reconstruction+3MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical Environments
Operating rooms (ORs) are complex, high-stakes environments requiring precise understanding of interactions among medical staff, tools, and equipment for enhancing surgical assistance, situational awareness, and patient …
2D Panoptic SegmentationGraph GenerationLanguage ModelingLanguage Modelling+2Pointmap Association and Piecewise-Plane Constraint for Consistent and Compact 3D Gaussian Segmentation Field
Achieving a consistent and compact 3D segmentation field is crucial for maintaining semantic coherence across views and accurately representing scene structures. Previous 3D scene segmentation methods rely on video segme…
2D Panoptic Segmentation3D Scene ReconstructionPanoptic SegmentationScene Segmentation+3In-Place Panoptic Radiance Field Segmentation with Perceptual Prior for 3D Scene Understanding
Accurate 3D scene representation and panoptic understanding are essential for applications such as virtual reality, robotics, and autonomous driving. However, challenges persist with existing methods, including precise 2…
2D Panoptic SegmentationAutonomous DrivingPanoptic 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+4Panoptic Compositional Feature Field for Editable Scene Rendering With Network-Inferred Labels via Metric Learning
Despite neural implicit representations demonstrating impressive high-quality view synthesis capacity, decomposing such representations into objects for instance-level editing is still challenging. Recent works learn…
2D Panoptic SegmentationMetric LearningNovel View SynthesisPanoptic SegmentationPanoptic Lifting for 3D Scene Understanding with Neural Fields
We propose Panoptic Lifting, a novel approach for learning panoptic 3D volumetric representations from images of in-the-wild scenes. Once trained, our model can render color images together with 3D-consistent panoptic se…
2D Panoptic SegmentationPanoptic SegmentationScene UnderstandingSegmentationPanoptic Neural Fields: A Semantic Object-Aware Neural Scene Representation
We present Panoptic Neural Fields (PNF), an object-aware neural scene representation that decomposes a scene into a set of objects (things) and background (stuff). Each object is represented by an oriented 3D bounding bo…
2D Panoptic Segmentation3D scene EditingDepth EstimationDepth Prediction+3Panoptic 3D Scene Reconstruction From a Single RGB Image
Understanding 3D scenes from a single image is fundamental to a wide variety of tasks, such as for robotics, motion planning, or augmented reality. Existing works in 3D perception from a single RGB image tend to focus on…
2D Panoptic Segmentation3D Instance Segmentation3D Scene Reconstruction3D Semantic Segmentation+6