跳至内容
  • 首页
  • 资讯
  • 行业方案
  • 付费阅读
  • Job招聘
  • Paper论文
  • Patent专利
  • 映维会员
  • 导航收录
  • 合作
  • 关于
  • 微信群
  • All
  • XR
  • CV
  • CG
  • HCI
  • Video
  • Optics
  • Perception
  • Reconstruction
空 挡 广 告 位 | 空 挡 广 告 位

In-Place Panoptic Radiance Field Segmentation with Perceptual Prior for 3D Scene Understanding

小编 广东客   |   分类:CV   |   2025年3月6日

Note: We don't have the ability to review paper

PubDate: Otc 2024

Teams:Shenghao Li

Writers: Shenghao Li

PDF:In-Place Panoptic Radiance Field Segmentation with Perceptual Prior for 3D Scene Understanding

Abstract

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 2D-to-3D mapping, handling complex scene characteristics like boundary ambiguity and varying scales, and mitigating noise in panoptic pseudo-labels. This paper introduces a novel perceptual-prior-guided 3D scene representation and panoptic understanding method, which reformulates panoptic understanding within neural radiance fields as a linear assignment problem involving 2D semantics and instance recognition. Perceptual information from pre-trained 2D panoptic segmentation models is incorporated as prior guidance, thereby synchronizing the learning processes of appearance, geometry, and panoptic understanding within neural radiance fields. An implicit scene representation and understanding model is developed to enhance generalization across indoor and outdoor scenes by extending the scale-encoded cascaded grids within a reparameterized domain distillation framework. This model effectively manages complex scene attributes and generates 3D-consistent scene representations and panoptic understanding outcomes for various scenes. Experiments and ablation studies under challenging conditions, including synthetic and real-world scenes, demonstrate the proposed method's effectiveness in enhancing 3D scene representation and panoptic segmentation accuracy.

本文链接:https://paper.nweon.com/16228

您可能还喜欢...

  • STaR: Self-supervised Tracking and Reconstruction of Rigid Objects in Motion with Neural Rendering

    2021年06月24日 映维

  • Back-tracing Representative Points for Voting-based3D Object Detection in Point Clouds

    2021年07月05日 映维

  • Dual sensor filtering for robust tracking of head-mounted displays

    2020年07月13日 映维

关注:

RSS 最新AR/VR行业分享

  • PlayStation VR Store 每周新内容 2025年6月1日
  • Steam VR每周新内容 2025年6月1日
  • Meta Store 每周新内容 2025年6月1日
  • PICO视频端午放送: 抖音汽水音乐节直播和六部新片上线 2025年5月31日
  • 传漫威将在下周推出“死侍”VR游戏 2025年5月31日

RSS 最新AR/VR专利

  • Sony Patent | Binary pattern transformation display 2025年5月29日
  • LG Patent | Organic light emitting diode display device and head mounted display including the same 2025年5月29日
  • Samsung Patent | Display device, method of manufacturing the display device, and head mounted display including the display device 2025年5月29日
  • Samsung Patent | Display device and head-mounted display device including the same 2025年5月29日
  • Samsung Patent | Display device 2025年5月29日

RSS 最新AR/VR行业招聘

  • Apple AR/VR Job | Senior Software QA Engineer - Apple Vision Pro 2024年11月12日
  • Apple AR/VR Job | System Product Design Engineer - Apple Vision Pro 2024年11月12日
  • Microsoft AR/VR Job | Principal Software Engineer -Teams Premium Services 2024年11月12日
  • Meta AR/VR Job | Software Engineer - XR Codec Interactions and Avatars Team 2024年11月12日
  • Meta AR/VR Job | Product Cost Engineer 2024年11月12日

联系微信:ovalics

版权所有:广州映维网络有限公司 © 2025

备案许可:粤ICP备17113731号-2

粤公网安备 44011302004835号

友情链接: AR/VR行业导航

读者QQ群:251118691

Quest QQ群:526200310

开发者QQ群:688769630

Paper