30 citations · 46 across the 9 of their papers we have counts for
9 papers
Text-Image Conditioned 3D Generation
Jiazhong Cen, Jiemin Fang, Sikuang Li +8
High-quality 3D assets are essential for VR/AR, industrial design, and entertainment, motivating growing interest in generative models that create 3D content from user prompts. Mos…
UniLat3D: Geometry-Appearance Unified Latents for Single-Stage 3D Generation
Guanjun Wu, Jiemin Fang, Chen Yang +11
High-fidelity 3D asset generation is crucial for various industries. While recent 3D pretrained models show strong capability in producing realistic content, most are built upon di…
Dynamic 2D Gaussians: Geometrically Accurate Radiance Fields for Dynamic Objects
Shuai Zhang, Guanjun Wu, Zhoufeng Xie +3
Reconstructing objects and extracting high-quality surfaces play a vital role in the real world. Current 4D representations show the ability to render high-quality novel views for…
Segment Any 4D Gaussians
Shengxiang Ji, Guanjun Wu, Jiemin Fang +5
Modeling, understanding, and reconstructing the real world are crucial in XR/VR. Recently, 3D Gaussian Splatting (3D-GS) methods have shown remarkable success in modeling and under…
GaussianDreamerPro: Text to Manipulable 3D Gaussians with Highly Enhanced Quality
Taoran Yi, Jiemin Fang, Zanwei Zhou +7
Recently, 3D Gaussian splatting (3D-GS) has achieved great success in reconstructing and rendering real-world scenes. To transfer the high rendering quality to generation tasks, a…
TOGS: Gaussian Splatting with Temporal Opacity Offset for Real-Time 4D DSA Rendering
Shuai Zhang, Huangxuan Zhao, Zhenghong Zhou +4
Four-dimensional Digital Subtraction Angiography (4D DSA) is a medical imaging technique that provides a series of 2D images captured at different stages and angles during the proc…
Fast High Dynamic Range Radiance Fields for Dynamic Scenes
Guanjun Wu, Taoran Yi, Jiemin Fang +2
Neural Radiances Fields (NeRF) and their extensions have shown great success in representing 3D scenes and synthesizing novel-view images. However, most NeRF methods take in low-dy…
GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Models
Taoran Yi, Jiemin Fang, Junjie Wang +6
In recent times, the generation of 3D assets from text prompts has shown impressive results. Both 2D and 3D diffusion models can help generate decent 3D objects based on prompts. 3…
4D Gaussian Splatting for Real-Time Dynamic Scene Rendering
Guanjun Wu, Taoran Yi, Jiemin Fang +6
Representing and rendering dynamic scenes has been an important but challenging task. Especially, to accurately model complex motions, high efficiency is usually hard to guarantee.…