1 code implementation • 19 Mar 2024 • Lingting Zhu, Noel Codella, Dongdong Chen, Zhenchao Jin, Lu Yuan, Lequan Yu
Our method begins with a 2D slice, noted as the informed slice to serve the patient prior, and propagates the generation process using a 3D segmentation mask.
1 code implementation • 21 Jan 2024 • Lingting Zhu, Zhao Wang, Jiahao Cui, Zhenchao Jin, Guying Lin, Lequan Yu
Specifically, our approach incorporates deformation fields to handle dynamic scenes, depth-guided supervision with spatial-temporal weight masks to optimize 3D targets with tool occlusion from a single viewpoint, and surface-aligned regularization terms to capture the much better geometry.
no code implementations • 18 Jan 2024 • Zhao Wang, Aoxue Li, Enze Xie, Lingting Zhu, Yong Guo, Qi Dou, Zhenguo Li
Customized text-to-video generation aims to generate high-quality videos guided by text prompts and subject references.
1 code implementation • NeurIPS 2023 • Zhenchao Jin, Xiaowei Hu, Lingting Zhu, Luchuan Song, Li Yuan, Lequan Yu
Next, a deletion diagnostics procedure is conducted to model relations of these semantic-level representations via perceiving the network outputs and the extracted relations are utilized to guide the semantic-level representations to interact with each other.
no code implementations • 27 Aug 2023 • Weijia Feng, Lingting Zhu, Lequan Yu
However, the adoption of foundational models in the medical domain presents a challenge due to the difficulty and expense of labeling sufficient data for adaptation within hospital systems.
no code implementations • 19 Jul 2023 • Lingting Zhu, Zeyue Xue, Zhenchao Jin, Xian Liu, Jingzhen He, Ziwei Liu, Lequan Yu
This paradigm extends the 2D image diffusion model to a volumetric version with a slightly increasing number of parameters and computation, offering a principled solution for generic cross-modality 3D medical image synthesis.
1 code implementation • CVPR 2023 • Lingting Zhu, Xian Liu, Xuanyu Liu, Rui Qian, Ziwei Liu, Lequan Yu
In this work, we propose a novel diffusion-based framework, named Diffusion Co-Speech Gesture (DiffGesture), to effectively capture the cross-modal audio-to-gesture associations and preserve temporal coherence for high-fidelity audio-driven co-speech gesture generation.