3 citations · 6 across the 12 of their papers we have counts for
13 papers
GAAT: Geometry-Aware Alignment Transformer for Multimodal UAV Perception
Jingpu Yang, Debin Tang, Yilin Sun +4
Unmanned aerial vehicle (UAV) multimodal perception integrates visible (RGB), infrared (IR), synthetic aperture radar (SAR), and depth sensors for scene understanding under diverse…
Chat-Edit-3D++: Interactive 3D and 4D Scene Editing via Large Language Models
Shuangkang Fang, Yufeng Wang, Yi-Hsuan Tsai +4
Recent work on image content manipulation based on vision-language pre-training models has been effectively extended to text-driven 3D scene editing. However, existing schemes for…
WaterClear-GS: Optical-Aware Gaussian Splatting for Underwater Reconstruction and Restoration
Xinrui Zhang, Yufeng Wang, Shuangkang Fang +3
Underwater 3D reconstruction and appearance restoration remain challenging due to the complex optical properties of water, such as wavelength-dependent attenuation and scattering.…
Frequency Point Game Environment for UAVs via Expert Knowledge and Large Language Model
Jingpu Yang, Hang Zhang, Fengxian Ji +4
Unmanned Aerial Vehicles (UAVs) have made significant advancements in communication stability and security through techniques such as frequency hopping, signal spreading, and adapt…
MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh
Shuangkang Fang, I-Chao Shen, Yufeng Wang +6
We present MeshLLM, a novel framework that leverages large language models (LLMs) to understand and generate text-serialized 3D meshes. Our approach addresses key limitations in ex…
NeRF Is a Valuable Assistant for 3D Gaussian Splatting
Shuangkang Fang, I-Chao Shen, Takeo Igarashi +5
We introduce NeRF-GS, a novel framework that jointly optimizes Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS). This framework leverages the inherent continuous spat…
Graph Structure Refinement with Energy-based Contrastive Learning
Xianlin Zeng, Yufeng Wang, Yuqi Sun +3
Graph Neural Networks (GNNs) have recently gained widespread attention as a successful tool for analyzing graph-structured data. However, imperfect graph structure with noisy links…
Multi-periodicity dependency Transformer based on spectrum offset for radio frequency fingerprint identification
Jing Xiao, Wenrui Ding, Zeqi Shao +4
Radio Frequency Fingerprint Identification (RFFI) has emerged as a pivotal task for reliable device authentication. Despite advancements in RFFI methods, background noise and inten…
Chat-Edit-3D: Interactive 3D Scene Editing via Text Prompts
Shuangkang Fang, Yufeng Wang, Yi-Hsuan Tsai +4
Recent work on image content manipulation based on vision-language pre-training models has been effectively extended to text-driven 3D scene editing. However, existing schemes for…
Editing 3D Scenes via Text Prompts without Retraining
Shuangkang Fang, Yufeng Wang, Yi Yang +4
Numerous diffusion models have recently been applied to image synthesis and editing. However, editing 3D scenes is still in its early stages. It poses various challenges, such as t…
Progressive Volume Distillation with Active Learning for Efficient NeRF Architecture Conversion
Shuangkang Fang, Yufeng Wang, Yi Yang +4
Neural Radiance Fields (NeRF) have been widely adopted as practical and versatile representations for 3D scenes, facilitating various downstream tasks. However, different architect…
Towards Accurate Binary Neural Networks via Modeling Contextual Dependencies
Xingrun Xing, Yangguang Li, Wei Li +6
Existing Binary Neural Networks (BNNs) mainly operate on local convolutions with binarization function. However, such simple bit operations lack the ability of modeling contextual…
Semi-supervised Multi-task Learning for Semantics and Depth
Yufeng Wang, Yi-Hsuan Tsai, Wei-Chih Hung +3
Multi-Task Learning (MTL) aims to enhance the model generalization by sharing representations between related tasks for better performance. Typical MTL methods are jointly trained…