activity
20162023
most citedMASC: Multi-scale Affinity with Sparse Convolution for 3D Instance Segmentation

81 citations · 349 across the 31 of their papers we have counts for

collaborators

32 papers

cs.CV2023★ 26 cited

MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion

Shitao Tang, Fuyang Zhang, Jiacheng Chen +2

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., perspecti…

cs.CV2023★ 9 cited

Hierarchical Neural Coding for Controllable CAD Model Generation

Xiang Xu, Pradeep Kumar Jayaraman, Joseph G. Lambourne +2

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 neur…

cs.CV2023★ 5 cited

PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models

Jiacheng Chen, Ruizhi Deng, Yasutaka Furukawa

This paper presents PolyDiffuse, a novel structured reconstruction algorithm that transforms visual sensor data into polygonal shapes with Diffusion Models (DM), an emerging machin…

cs.CV2023★ 1 cited

Hierarchical Neural Memory Network for Low Latency Event Processing

Ryuhei Hamaguchi, Yasutaka Furukawa, Masaki Onishi +1

This paper proposes a low latency neural network architecture for event-based dense prediction tasks. Conventional architectures encode entire scene contents at a fixed rate regard…

cs.CV2022★ 7 cited

HouseDiffusion: Vector Floorplan Generation via a Diffusion Model with Discrete and Continuous Denoising

Mohammad Amin Shabani, Sepidehsadat Hosseini, Yasutaka Furukawa

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 si…

cs.AI2022★ 4 cited

PuzzleFusion: Unleashing the Power of Diffusion Models for Spatial Puzzle Solving

Sepidehsadat Hosseini, Mohammad Amin Shabani, Saghar Irandoust +1

This paper presents an end-to-end neural architecture based on Diffusion Models for spatial puzzle solving, particularly jigsaw puzzle and room arrangement tasks. In the latter tas…

cs.CV2022★ 2 cited

NeuMap: Neural Coordinate Mapping by Auto-Transdecoder for Camera Localization

Shitao Tang, Sicong Tang, Andrea Tagliasacchi +2

This paper presents an end-to-end neural mapping method for camera localization, dubbed NeuMap, encoding a whole scene into a grid of latent codes, with which a Transformer-based a…

cs.CV2022★ 13 cited

SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks

Xiang Xu, Karl D. D. Willis, Joseph G. Lambourne +3

We present SkexGen, a novel autoregressive generative model for computer-aided design (CAD) construction sequences containing sketch-and-extrude modeling operations. Our model util…

cs.CV2022★ 1 cited

Floorplan Restoration by Structure Hallucinating Transformer Cascades

Sepidehsadat Hosseini, Yasutaka Furukawa

This paper presents an extreme floorplan reconstruction task, a new benchmark for the task, and a neural architecture as a solution. Given a partial floorplan reconstruction inferr…

cs.RO2022

Neural Inertial Localization

Sachini Herath, David Caruso, Chen Liu +2

This paper proposes the inertial localization problem, the task of estimating the absolute location from a sequence of inertial sensor measurements. This is an exciting and unexplo…

cs.CV2021

HEAT: Holistic Edge Attention Transformer for Structured Reconstruction

Jiacheng Chen, Yiming Qian, Yasutaka Furukawa

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 und…

cs.CV2021

Structured Outdoor Architecture Reconstruction by Exploration and Classification

Fuyang Zhang, Xiang Xu, Nelson Nauata +1

This paper presents an explore-and-classify framework for structured architectural reconstruction from an aerial image. Starting from a potentially imperfect building reconstructio…

cs.CV2021

Plan2Scene: Converting Floorplans to 3D Scenes

Madhawa Vidanapathirana, Qirui Wu, Yasutaka Furukawa +2

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. Our system 1) lifts a fl…

cs.RO2021★ 4 cited

Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments

Sachini Herath, Saghar Irandoust, Bowen Chen +3

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. The…

cs.CV2021

Heterogeneous Grid Convolution for Adaptive, Efficient, and Controllable Computation

Ryuhei Hamaguchi, Yasutaka Furukawa, Masaki Onishi +1

This paper proposes a novel heterogeneous grid convolution that builds a graph-based image representation by exploiting heterogeneity in the image content, enabling adaptive, effic…

cs.CV2021★ 20 cited

House-GAN++: Generative Adversarial Layout Refinement Networks

Nelson Nauata, Sepidehsadat Hosseini, Kai-Hung Chang +3

This paper proposes a novel generative adversarial layout refinement network for automated floorplan generation. Our architecture is an integration of a graph-constrained relationa…

cs.CV2020★ 6 cited

Roof-GAN: Learning to Generate Roof Geometry and Relations for Residential Houses

Yiming Qian, Hao Zhang, Yasutaka Furukawa

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 relatio…

cs.CV2020★ 29 cited

House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation

Nelson Nauata, Kai-Hung Chang, Chin-Yi Cheng +2

This paper proposes a novel graph-constrained generative adversarial network, whose generator and discriminator are built upon relational architecture. The main idea is to encode t…

cs.CV2019★ 5 cited

Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Inference

Nelson Nauata, Yasutaka Furukawa

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. We provide a new b…

cs.CV2019★ 5 cited

Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction

Fuyang Zhang, Nelson Nauata, Yasutaka Furukawa

This paper proposes a novel message passing neural (MPN) architecture Conv-MPN, which reconstructs an outdoor building as a planar graph from a single RGB image. Conv-MPN is specif…

cs.CV2019★ 7 cited

Floor-SP: Inverse CAD for Floorplans by Sequential Room-wise Shortest Path

Jiacheng Chen, Chen Liu, Jiaye Wu +1

This paper proposes a new approach for automated floorplan reconstruction from RGBD scans, a major milestone in indoor mapping research. The approach, dubbed Floor-SP, formulates a…

cs.CV2019★ 36 cited

RoNIN: Robust Neural Inertial Navigation in the Wild: Benchmark, Evaluations, and New Methods

Hang Yan, Sachini Herath, Yasutaka Furukawa

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…

cs.CV2019★ 81 cited

MASC: Multi-scale Affinity with Sparse Convolution for 3D Instance Segmentation

Chen Liu, Yasutaka Furukawa

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…

cs.CV2019★ 6 cited

PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Image

Chen Liu, Kihwan Kim, Jinwei Gu +2

This paper proposes a deep neural architecture, PlaneRCNN, that detects and reconstructs piecewise planar surfaces from a single RGB image. PlaneRCNN employs a variant of Mask R-CN…