3 citations · 5 across the 10 of their papers we have counts for
11 papers
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…
Dropping Anchor and Spherical Harmonics for Sparse-view Gaussian Splatting
Shuangkang Fang, I-Chao Shen, Xuanyang Zhang +5
Recent 3D Gaussian Splatting (3DGS) Dropout methods address overfitting under sparse-view conditions by randomly nullifying Gaussian opacities. However, we identify a neighbor comp…
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.…
Native 3D Editing with Full Attention
Weiwei Cai, Shuangkang Fang, Weicai Ye +7
Instruction-guided 3D editing is a rapidly emerging field with the potential to broaden access to 3D content creation. However, existing methods face critical limitations: optimiza…
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…
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…
One is All: Bridging the Gap Between Neural Radiance Fields Architectures with Progressive Volume Distillation
Shuangkang Fang, Weixin Xu, Heng Wang +3
Neural Radiance Fields (NeRF) methods have proved effective as compact, high-quality and versatile representations for 3D scenes, and enable downstream tasks such as editing, retri…
Arch-Net: Model Distillation for Architecture Agnostic Model Deployment
Weixin Xu, Zipeng Feng, Shuangkang Fang +3
Vast requirement of computation power of Deep Neural Networks is a major hurdle to their real world applications. Many recent Application Specific Integrated Circuit (ASIC) chips f…