Search Results for author:
Found 45 papers, 28 papers with code
Learning Pairwise Inter-Plane Relations for Piecewise Planar Reconstruction
This paper proposes a novel single-image piecewise planar reconstruction technique that infers and enforces inter-plane relationships.
MapTracker: Tracking with Strided Memory Fusion for Consistent Vector HD Mapping
The paper further makes benchmark contributions by 1) Improving processing code for existing datasets to produce consistent ground truth with temporal alignments and 2) Augmenting existing mAP metrics with consistency checks.
MVDiffusion++: A Dense High-resolution Multi-view Diffusion Model for Single or Sparse-view 3D Object Reconstruction
MVDiffusion++ achieves superior flexibility and scalability with two surprisingly simple ideas: 1) A ``pose-free architecture'' where standard self-attention among 2D latent features learns 3D consistency across an arbitrary number of conditional and generation views without explicitly using camera pose information; and 2) A ``view dropout strategy'' that discards a substantial number of output views during training, which reduces the training-time memory footprint and enables dense and high-resolution view synthesis at test time.
BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometry
Starting from the root and progressing to the leaf, BrepGen employs Transformer-based diffusion models to sequentially denoise node features while duplicated nodes are detected and merged, recovering the B-Rep topology information.
A-Scan2BIM: Assistive Scan to Building Information Modeling
This paper proposes an assistive system for architects that converts a large-scale point cloud into a standardized digital representation of a building for Building Information Modeling (BIM) applications.
MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion
This paper introduces MVDiffusion, a simple yet effective method for generating consistent multi-view images from text prompts given pixel-to-pixel correspondences (e. g., perspective crops from a panorama or multi-view images given depth maps and poses).
Hierarchical Neural Coding for Controllable CAD Model Generation
This paper presents a novel generative model for Computer Aided Design (CAD) that 1) represents high-level design concepts of a CAD model as a three-level hierarchical tree of neural codes, from global part arrangement down to local curve geometry; and 2) controls the generation or completion of CAD models by specifying the target design using a code tree.
PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models
This paper presents PolyDiffuse, a novel structured reconstruction algorithm that transforms visual sensor data into polygonal shapes with Diffusion Models (DM), an emerging machinery amid exploding generative AI, while formulating reconstruction as a generation process conditioned on sensor data.
Hierarchical Neural Memory Network for Low Latency Event Processing
Conventional architectures encode entire scene contents at a fixed rate regardless of their temporal characteristics.
Ranked #2 on
Object Detection
on GEN1 Detection
HouseDiffusion: Vector Floorplan Generation via a Diffusion Model with Discrete and Continuous Denoising
The paper presents a novel approach for vector-floorplan generation via a diffusion model, which denoises 2D coordinates of room/door corners with two inference objectives: 1) a single-step noise as the continuous quantity to precisely invert the continuous forward process; and 2) the final 2D coordinate as the discrete quantity to establish geometric incident relationships such as parallelism, orthogonality, and corner-sharing.
NeuMap: Neural Coordinate Mapping by Auto-Transdecoder for Camera Localization
State-of-the-art feature matching methods require each scene to be stored as a 3D point cloud with per-point features, consuming several gigabytes of storage per scene.
SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks
We present SkexGen, a novel autoregressive generative model for computer-aided design (CAD) construction sequences containing sketch-and-extrude modeling operations.
Floorplan Restoration by Structure Hallucinating Transformer Cascades
This paper presents an extreme floorplan reconstruction task, a new benchmark for the task, and a neural architecture as a solution.
Neural Inertial Localization
This paper proposes the inertial localization problem, the task of estimating the absolute location from a sequence of inertial sensor measurements.
HEAT: Holistic Edge Attention Transformer for Structured Reconstruction
This paper presents a novel attention-based neural network for structured reconstruction, which takes a 2D raster image as an input and reconstructs a planar graph depicting an underlying geometric structure.
Edge Classification
Extracting Buildings In Remote Sensing Images
+1
Structured Outdoor Architecture Reconstruction by Exploration and Classification
This paper presents an explore-and-classify framework for structured architectural reconstruction from an aerial image.
House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects
This paper proposes a generative adversarial layout refinement network for automated floorplan generation.
Plan2Scene: Converting Floorplans to 3D Scenes
We address the task of converting a floorplan and a set of associated photos of a residence into a textured 3D mesh model, a task which we call Plan2Scene.
Ranked #1 on
Plan2Scene
on Rent3D++
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments
The paper proposes a multi-modal sensor fusion algorithm that fuses WiFi, IMU, and floorplan information to infer an accurate and dense location history in indoor environments.
Heterogeneous Grid Convolution for Adaptive, Efficient, and Controllable Computation
This paper proposes a novel heterogeneous grid convolution that builds a graph-based image representation by exploiting heterogeneity in the image content, enabling adaptive, efficient, and controllable computations in a convolutional architecture.
House-GAN++: Generative Adversarial Layout Refinement Networks
This paper proposes a novel generative adversarial layout refinement network for automated floorplan generation.
Extreme Structure From Motion for Indoor Panoramas Without Visual Overlaps
We evaluate the proposed approach on a dataset of 1029 panorama images with 286 houses.
Roof-GAN: Learning to Generate Roof Geometry and Relations for Residential Houses
This paper presents Roof-GAN, a novel generative adversarial network that generates structured geometry of residential roof structures as a set of roof primitives and their relationships.
House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation
This paper proposes a novel graph-constrained generative adversarial network, whose generator and discriminator are built upon relational architecture.
Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Inference
This paper tackles a 2D architecture vectorization problem, whose task is to infer an outdoor building architecture as a 2D planar graph from a single RGB image.
Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction
In our problem, nodes correspond to building edges in an image.
Floor-SP: Inverse CAD for Floorplans by Sequential Room-wise Shortest Path
This paper proposes a new approach for automated floorplan reconstruction from RGBD scans, a major milestone in indoor mapping research.
RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, and New Methods
This paper sets a new foundation for data-driven inertial navigation research, where the task is the estimation of positions and orientations of a moving subject from a sequence of IMU sensor measurements.
MASC: Multi-scale Affinity with Sparse Convolution for 3D Instance Segmentation
We propose a new approach for 3D instance segmentation based on sparse convolution and point affinity prediction, which indicates the likelihood of two points belonging to the same instance.
Ranked #1 on
3D Instance Segmentation
on ScanNet
PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image
This paper proposes a deep neural architecture, PlaneRCNN, that detects and reconstructs piecewise planar surfaces from a single RGB image.
Neural Procedural Reconstruction for Residential Buildings
This paper proposes a novel 3D reconstruction approach, dubbed Neural Procedural Reconstruction (NPR), which trains deep neural networks to procedurally apply shape grammar rules and reconstruct CAD-quality models from 3D points.
Polarimetric Dense Monocular SLAM
This paper presents a novel polarimetric dense monocular SLAM (PDMS) algorithm based on a polarization camera.
PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image
The proposed end-to-end DNN learns to directly infer a set of plane parameters and corresponding plane segmentation masks from a single RGB image.
Ranked #2 on
Plane Instance Segmentation
on NYU Depth v2
FloorNet: A Unified Framework for Floorplan Reconstruction from 3D Scans
The ultimate goal of this indoor mapping research is to automatically reconstruct a floorplan simply by walking through a house with a smartphone in a pocket.
RIDI: Robust IMU Double Integration
This paper proposes a novel data-driven approach for inertial navigation, which learns to estimate trajectories of natural human motions just from an inertial measurement unit (IMU) in every smartphone.
Raster-To-Vector: Revisiting Floorplan Transformation
A neural architecture first transforms a rasterized image to a set of junctions that represent low-level geometric and semantic information (e. g., wall corners or door end-points).
Exploiting 2D Floorplan for Building-scale Panorama RGBD Alignment
To the best of our knowledge, we present the first effective system that utilizes a 2D floorplan image for building-scale 3D pointcloud alignment.
Turning an Urban Scene Video into a Cinemagraph
Our approach first warps an input video into the viewpoint of a reference camera.
Panoramic Structure from Motion via Geometric Relationship Detection
This paper addresses the problem of Structure from Motion (SfM) for indoor panoramic image streams, extremely challenging even for the state-of-the-art due to the lack of textures and minimal parallax.
Multi-way Particle Swarm Fusion
This paper proposes a novel MAP inference framework for Markov Random Field (MRF) in parallel computing environments.
Deep Multi-Modal Image Correspondence Learning
Our result implies that neural networks are effective at perceptual tasks that require long periods of reasoning even for humans to solve.
Layered Scene Decomposition via the Occlusion-CRF
This paper addresses the challenging problem of perceiving the hidden or occluded geometry of the scene depicted in any given RGBD image.
Structured Indoor Modeling
The grammar then drives a principled new reconstruction algorithm, where the grammar rules are sequentially applied to recover a structured model.
Piecewise Planar and Compact Floorplan Reconstruction from Images
The second challenge is the need of a sophisti- cated regularization technique that enforces piecewise pla- narity, to suppress clutter and yield high quality texture mapped models.
Occluding Contours for Multi-View Stereo
The proposed approach outperforms state of the art MVS techniques for challenging Internet datasets, yielding dramatic quality improvements both around object contours and in surface detail.
