Search Results for author: Rao Fu

Found 18 papers, 11 papers with code

Scene-LLM: Extending Language Model for 3D Visual Understanding and Reasoning

no code implementations18 Mar 2024 Rao Fu, Jingyu Liu, Xilun Chen, Yixin Nie, Wenhan Xiong

This paper introduces Scene-LLM, a 3D-visual-language model that enhances embodied agents' abilities in interactive 3D indoor environments by integrating the reasoning strengths of Large Language Models (LLMs).

Dense Captioning Language Modelling +1

Deep Generative Modeling for Financial Time Series with Application in VaR: A Comparative Review

no code implementations18 Jan 2024 Lars Ericson, Xuejun Zhu, Xusi Han, Rao Fu, Shuang Li, Steve Guo, Ping Hu

The objectives for financial time series generation are to generate synthetic data paths with good variety, and similar distribution and dynamics to the original historical data.

Time Series Time Series Generation

AnyHome: Open-Vocabulary Generation of Structured and Textured 3D Homes

no code implementations11 Dec 2023 Rao Fu, Zehao Wen, Zichen Liu, Srinath Sridhar

Inspired by cognitive theories, we introduce AnyHome, a framework that translates any text into well-structured and textured indoor scenes at a house-scale.

Patch-Wise Point Cloud Generation: A Divide-and-Conquer Approach

1 code implementation22 Jul 2023 Cheng Wen, Baosheng Yu, Rao Fu, DaCheng Tao

A generative model for high-fidelity point clouds is of great importance in synthesizing 3d environments for applications such as autonomous driving and robotics.

Autonomous Driving Point Cloud Generation

BPNet: Bézier Primitive Segmentation on 3D Point Clouds

1 code implementation8 Jul 2023 Rao Fu, Cheng Wen, Qian Li, Xiao Xiao, Pierre Alliez

This paper proposes BPNet, a novel end-to-end deep learning framework to learn B\'ezier primitive segmentation on 3D point clouds.

Point Cloud Segmentation Segmentation

Simplifying Low-Light Image Enhancement Networks with Relative Loss Functions

1 code implementation6 Apr 2023 Yu Zhang, Xiaoguang Di, Junde Wu, Rao Fu, Yong Li, Yue Wang, Yanwu Xu, Guohui YANG, Chunhui Wang

In this paper, to make the learning easier in low-light image enhancement, we introduce FLW-Net (Fast and LightWeight Network) and two relative loss functions.

Low-Light Image Enhancement

MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model

2 code implementations1 Nov 2022 Junde Wu, Rao Fu, Huihui Fang, Yu Zhang, Yehui Yang, Haoyi Xiong, Huiying Liu, Yanwu Xu

Inspired by the success of DPM, we propose the first DPM based model toward general medical image segmentation tasks, which we named MedSegDiff.

Anomaly Detection Brain Tumor Segmentation +8

An Efficient Person Clustering Algorithm for Open Checkout-free Groceries

1 code implementation5 Aug 2022 Junde Wu, Yu Zhang, Rao Fu, Yuanpei Liu, Jing Gao

Then, to ensure that the method adapts to the dynamic and unseen person flow, we propose Graph Convolutional Network (GCN) with a simple Nearest Neighbor (NN) strategy to accurately cluster the instances of CSG.

Clustering

ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model

1 code implementation19 Jul 2022 Rao Fu, Xiao Zhan, YiWen Chen, Daniel Ritchie, Srinath Sridhar

Results show that our method can generate shapes consistent with text descriptions, and shapes evolve gradually as more phrases are added.

3D Shape Generation

NeuralODF: Learning Omnidirectional Distance Fields for 3D Shape Representation

no code implementations12 Jun 2022 Trevor Houchens, Cheng-You Lu, Shivam Duggal, Rao Fu, Srinath Sridhar

We propose Omnidirectional Distance Fields (ODFs), a new 3D shape representation that encodes geometry by storing the depth to the object's surface from any 3D position in any viewing direction.

3D Shape Representation

HRFormer: High-Resolution Vision Transformer for Dense Predict

2 code implementations NeurIPS 2021 Yuhui Yuan, Rao Fu, Lang Huang, WeiHong Lin, Chao Zhang, Xilin Chen, Jingdong Wang

We present a High-Resolution Transformer (HRFormer) that learns high-resolution representations for dense prediction tasks, in contrast to the original Vision Transformer that produces low-resolution representations and has high memory and computational cost.

Pose Estimation Semantic Segmentation +1

HRFormer: High-Resolution Transformer for Dense Prediction

1 code implementation18 Oct 2021 Yuhui Yuan, Rao Fu, Lang Huang, WeiHong Lin, Chao Zhang, Xilin Chen, Jingdong Wang

We present a High-Resolution Transformer (HRFormer) that learns high-resolution representations for dense prediction tasks, in contrast to the original Vision Transformer that produces low-resolution representations and has high memory and computational cost.

Image Classification Multi-Person Pose Estimation +2

Query-aware Tip Generation for Vertical Search

no code implementations19 Oct 2020 Yang Yang, Junmei Hao, Canjia Li, Zili Wang, Jingang Wang, Fuzheng Zhang, Rao Fu, Peixu Hou, Gong Zhang, Zhongyuan Wang

Existing work on tip generation does not take query into consideration, which limits the impact of tips in search scenarios.

Decision Making

RISA-Net: Rotation-Invariant Structure-Aware Network for Fine-Grained 3D Shape Retrieval

1 code implementation2 Oct 2020 Rao Fu, Jie Yang, Jiawei Sun, Fang-Lue Zhang, Yu-Kun Lai, Lin Gao

Fine-grained 3D shape retrieval aims to retrieve 3D shapes similar to a query shape in a repository with models belonging to the same class, which requires shape descriptors to be capable of representing detailed geometric information to discriminate shapes with globally similar structures.

3D Object Retrieval 3D Shape Retrieval +1

Leveraging Undiagnosed Data for Glaucoma Classification with Teacher-Student Learning

1 code implementation22 Jul 2020 Junde Wu, Shuang Yu, WenTing Chen, Kai Ma, Rao Fu, Hanruo Liu, Xiaoguang Di, Yefeng Zheng

Recently, deep learning has been adopted to the glaucoma classification task with performance comparable to that of human experts.

Classification General Classification +1

Universal, transferable and targeted adversarial attacks

1 code implementation29 Aug 2019 Junde Wu, Rao Fu

The question is: Is there existan attack that can meet all these requirements?

Time Series Simulation by Conditional Generative Adversarial Net

no code implementations25 Apr 2019 Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

Generative Adversarial Net (GAN) has been proven to be a powerful machine learning tool in image data analysis and generation.

Time Series Time Series Analysis

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