Search Results for author: Yuan Huang

Found 22 papers, 9 papers with code

UrbanCraft: Urban View Extrapolation via Hierarchical Sem-Geometric Priors

no code implementations29 May 2025 Tianhang Wang, Fan Lu, Sanqing Qu, Guo Yu, Shihang Du, Ya Wu, Yuan Huang, Guang Chen

Existing neural rendering-based urban scene reconstruction methods mainly focus on the Interpolated View Synthesis (IVS) setting that synthesizes from views close to training camera trajectory.

Neural Rendering

A New Segment Routing method with Swap Node Selection Strategy Based on Deep Reinforcement Learning for Software Defined Network

no code implementations21 Mar 2025 Miao Ye, Jihao Zheng, Qiuxiang Jiang, Yuan Huang, Ziheng Wang, Yong Wang

The existing segment routing (SR) methods need to determine the routing first and then use path segmentation approaches to select swap nodes to form a segment routing path (SRP).

Deep Reinforcement Learning

Geolocation with Real Human Gameplay Data: A Large-Scale Dataset and Human-Like Reasoning Framework

1 code implementation19 Feb 2025 Zirui Song, Jingpu Yang, Yuan Huang, Jonathan Tonglet, Zeyu Zhang, Tao Cheng, Meng Fang, Iryna Gurevych, Xiuying Chen

To address these challenges, we introduce a comprehensive geolocation framework with three key components: GeoComp, a large-scale dataset; GeoCoT, a novel reasoning method; and GeoEval, an evaluation metric, collectively designed to address critical challenges and drive advancements in geolocation research.

Range and Bird's Eye View Fused Cross-Modal Visual Place Recognition

1 code implementation17 Feb 2025 Jianyi Peng, Fan Lu, Bin Li, Yuan Huang, Sanqing Qu, Guang Chen

Compared to single-modal VPR, this approach benefits from the widespread availability of RGB cameras and the robustness of point clouds in providing accurate spatial geometry and distance information.

Re-Ranking Triplet +1

Vevo: Controllable Zero-Shot Voice Imitation with Self-Supervised Disentanglement

no code implementations11 Feb 2025 Xueyao Zhang, Xiaohui Zhang, Kainan Peng, Zhenyu Tang, Vimal Manohar, Yingru Liu, Jeff Hwang, Dangna Li, Yuhao Wang, Julian Chan, Yuan Huang, Zhizheng Wu, Mingbo Ma

However, existing methods rely heavily on annotated data, and struggle with effectively disentangling timbre and style, leading to challenges in achieving controllable generation, especially in zero-shot scenarios.

Disentanglement text-to-speech +2

Review and Recommendations for using Artificial Intelligence in Intracoronary Optical Coherence Tomography Analysis

no code implementations24 Jan 2025 Xu Chen, Yuan Huang, Benn Jessney, Jason Sangha, Sophie Gu, Carola-Bibiane Schönlieb, Martin Bennett, Michael Roberts

Artificial intelligence (AI) methodologies hold great promise for the rapid and accurate diagnosis of coronary artery disease (CAD) from intravascular optical coherent tomography (IVOCT) images.

Diagnostic

Review of wavelet-based unsupervised texture segmentation, advantage of adaptive wavelets

no code implementations24 Oct 2024 Yuan Huang, Valentin De Bortoli, Fugen Zhou, Jerome Gilles

Wavelet-based segmentation approaches are widely used for texture segmentation purposes because of their ability to characterize different textures.

Segmentation

MMAC-Copilot: Multi-modal Agent Collaboration Operating Copilot

no code implementations28 Apr 2024 Zirui Song, Yaohang Li, Meng Fang, Yanda Li, Zhenhao Chen, Zecheng Shi, Yuan Huang, Xiuying Chen, Ling Chen

To address this, we propose the Multi-Modal Agent Collaboration framework (MMAC-Copilot), a framework utilizes the collective expertise of diverse agents to enhance interaction ability with application.

Hallucination Language Modeling +2

End-to-end Rain Streak Removal with RAW Images

no code implementations20 Dec 2023 Guodong Du, HaoJian Deng, Jiahao Su, Yuan Huang

To be specific, we generate rainy RAW data by converting color rain streak into RAW space and design simple but efficient RAW processing algorithms to synthesize both rainy and clean color images.

Rain Removal

Does VLN Pretraining Work with Nonsensical or Irrelevant Instructions?

no code implementations28 Nov 2023 Wang Zhu, Ishika Singh, Yuan Huang, Robin Jia, Jesse Thomason

Data augmentation via back-translation is common when pretraining Vision-and-Language Navigation (VLN) models, even though the generated instructions are noisy.

Data Augmentation Translation +1

TextSLAM: Visual SLAM with Semantic Planar Text Features

1 code implementation17 May 2023 Boying Li, Danping Zou, Yuan Huang, Xinghan Niu, Ling Pei, Wenxian Yu

The results show that integrating texture features leads to a more superior SLAM system that can match images across day and night.

Mixed Reality Object SLAM +2

Exploring Representation-Level Augmentation for Code Search

1 code implementation21 Oct 2022 Haochen Li, Chunyan Miao, Cyril Leung, Yanxian Huang, Yuan Huang, Hongyu Zhang, Yanlin Wang

In this paper, we explore augmentation methods that augment data (both code and query) at representation level which does not require additional data processing and training, and based on this we propose a general format of representation-level augmentation that unifies existing methods.

Code Search Contrastive Learning +1

Air Quality Prediction Using Improved PSO-BP Neural Network

no code implementations28 May 2020 Yuan Huang, YUXING XIANG, RUIXIAO ZHAO, AND ZHE CHEN

Predicting urban air quality is a significant aspect of preventing urban air pollution and improving the living environment of urban residents.

Noisy-As-Clean: Learning Self-supervised Denoising from the Corrupted Image

1 code implementation17 Jun 2019 Jun Xu, Yuan Huang, Ming-Ming Cheng, Li Liu, Fan Zhu, Zhou Xu, Ling Shao

A simple but useful observation on our NAC is: as long as the noise is weak, it is feasible to learn a self-supervised network only with the corrupted image, approximating the optimal parameters of a supervised network learned with pairs of noisy and clean images.

Image Denoising

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