30 open-source projects similar to waldjohannau/3rscan, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.
The 2D-3D-S dataset provides a variety of mutually registered modalities from 2D, 2.5D and 3D domains, with instance-level semantic and geometric annotations. It covers over 6,000 m2 collected in 6 large-scale indoor areas that originate from 3 different buildings. It contains over 70,000 RGB…
Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image
Official implementation for Learning Multi-View Aggregation In the Wild for Large-Scale 3D Semantic Segmentation (CVPR'22 Best Paper Finalist 🎉) If you ❤️ or simply use this project, don't forget to give the repository a ⭐, it means a lot to us !
Habitat-sim is a high-performance 3D simulation platform designed for training and benchmarking embodied AI agents within photorealistic indoor and outdoor environments. It serves as a simulator for AI and robotics, providing a system for generating synthetic data and simulating physical interactions. The project is distinguished by a native C++ core that enables high-throughput simulation and a rendering pipeline using physically based rendering and baked global illumination. It features a navigation system based on pre-computed navigation meshes to ensure collision-free traversal and a rigi
The Replica Dataset is a dataset of high quality reconstructions of a variety of indoor spaces. Each reconstruction has clean dense geometry, high resolution and high dynamic range textures, glass and mirror surface information, planar segmentation as well as semantic class and instance…
Properties of dilated convolution are discussed in our ICLR 2016 conference paper. This repository contains the network definitions and the trained models. You can use this code together with vanilla Caffe to segment images using the pre-trained models. If you want to train the models yourself,…
This repository serves as a comprehensive research platform and toolkit for advancing machine learning, quantum computing, and large-scale scientific data analysis. It provides foundational frameworks for developing complex algorithmic systems, offering the necessary infrastructure for distributed training, computational graph execution, and high-performance model development. The project distinguishes itself by integrating specialized research domains with robust, privacy-preserving methodologies. It supports diverse scientific discovery through tools for quantum simulation, physics-informed
This repository contains pre-trained models and evaluation code for the project 'Single Image 3D Interpreter Network' (ECCV 2016).
Free-form Description-guided 3D Visual Graph Networks for Object Grounding in Point Cloud
🔥RandLA-Net in Tensorflow (CVPR 2020, Oral & IEEE TPAMI 2021)
This is the official repository of the Semantic Query Network (SQN). For technical details, please refer to:
This is the implementation of our CVPRW'21 paper " OmniLayout: Room Layout Reconstruction from Indoor Spherical Panoramas " accepted at the 2nd workshop on Omnidirectional Computer Vision.
ScanNet is an RGB-D video dataset containing 2.5 million views in more than 1500 scans, annotated with 3D camera poses, surface reconstructions, and instance-level semantic segmentations.
This repo contains training and testing code for our paper on semantic scene completion, a task for producing a complete 3D voxel representation of volumetric occupancy and semantic labels for a scene from a single-view depth map observation. More information about the project can be found in…
PyTorch implementation of our CVPR 2019 paper:
The official implementation of PhotoScene: Photorealistic Material and Lighting Transfer for Indoor Scenes. Yu-Ying Yeh, Zhengqin Li, Yannick Hold-Geoffroy, Rui Zhu, Zexiang Xu, Miloš Hašan, Kalyan Sunkavalli, Manmohan Chandraker IEEE / CVF Computer Vision and Pattern Recognition Conference…
The source code of our work "Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation
Official code for "Structured Bird’s-Eye-View Traffic Scene Understanding from Onboard Images" (ICCV 2021)
This package includes the whole pipeline for generating physically based rendering synthetic data for indoor scene understanding. We also provide download links for most of the intermediate and final results. Please refer to the project webpage (http://pbrs.cs.princeton.edu) for more details.