12 citations · 17 across the 12 of their papers we have counts for
5 papers · 1 filter
ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model
Fangfu Liu, Wenqiang Sun, Hanyang Wang +5
Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great s…
DreamCinema: Cinematic Transfer with Free Camera and 3D Character
Weiliang Chen, Fangfu Liu, Diankun Wu +3
We are living in a flourishing era of digital media, where everyone has the potential to become a personal filmmaker. Current research on video generation suggests a promising aven…
LGTM: Local-to-Global Text-Driven Human Motion Diffusion Model
Haowen Sun, Ruikun Zheng, Haibin Huang +3
In this paper, we introduce LGTM, a novel Local-to-Global pipeline for Text-to-Motion generation. LGTM utilizes a diffusion-based architecture and aims to address the challenge of…
Make-Your-3D: Fast and Consistent Subject-Driven 3D Content Generation
Fangfu Liu, Hanyang Wang, Weiliang Chen +2
Recent years have witnessed the strong power of 3D generation models, which offer a new level of creative flexibility by allowing users to guide the 3D content generation process t…
InterFusion: Text-Driven Generation of 3D Human-Object Interaction
Sisi Dai, Wenhao Li, Haowen Sun +5
In this study, we tackle the complex task of generating 3D human-object interactions (HOI) from textual descriptions in a zero-shot text-to-3D manner. We identify and address two k…