3 citations · 4 across the 6 of their papers we have counts for
8 papers
Breaking the Vicious Cycle: Coherent 3D Gaussian Splatting from Sparse and Motion-Blurred Views
Zhankuo Xu, Chaoran Feng, Yingtao Li +5
3D Gaussian Splatting (3DGS) has emerged as a state-of-the-art method for novel view synthesis. However, its performance heavily relies on dense, high-quality input imagery, an ass…
Uniworld-V2: Reinforce Image Editing with Diffusion Negative-aware Finetuning and MLLM Implicit Feedback
Zongjian Li, Zheyuan Liu, Qihui Zhang +10
Instruction-based image editing has achieved remarkable progress; however, models solely trained via supervised fine-tuning often overfit to annotated patterns, hindering their abi…
E-4DGS: High-Fidelity Dynamic Reconstruction from the Multi-view Event Cameras
Chaoran Feng, Zhenyu Tang, Wangbo Yu +5
Novel view synthesis and 4D reconstruction techniques predominantly rely on RGB cameras, thereby inheriting inherent limitations such as the dependence on adequate lighting, suscep…
UniWorld-V1: High-Resolution Semantic Encoders for Unified Visual Understanding and Generation
Bin Lin, Zongjian Li, Xinhua Cheng +9
Although existing unified models achieve strong performance in vision-language understanding and text-to-image generation, they remain limited in addressing image perception and ma…
GS2E: Gaussian Splatting is an Effective Data Generator for Event Stream Generation
Yuchen Li, Chaoran Feng, Zhenyu Tang +4
We introduce GS2E (Gaussian Splatting to Event), a large-scale synthetic event dataset for high-fidelity event vision tasks, captured from real-world sparse multi-view RGB images.…
HoloTime: Taming Video Diffusion Models for Panoramic 4D Scene Generation
Haiyang Zhou, Wangbo Yu, Jiawen Guan +3
The rapid advancement of diffusion models holds the promise of revolutionizing the application of VR and AR technologies, which typically require scene-level 4D assets for user exp…