Search Results for author: Yamin Li

Found 9 papers, 2 papers with code

DaReNeRF: Direction-aware Representation for Dynamic Scenes

no code implementations CVPR 2024 Ange Lou, Benjamin Planche, Zhongpai Gao, Yamin Li, Tianyu Luan, Hao Ding, Terrence Chen, Jack Noble, Ziyan Wu

However, the straightforward decomposition of 4D dynamic scenes into multiple 2D plane-based representations proves insufficient for re-rendering high-fidelity scenes with complex motions.

Novel View Synthesis

Leveraging sinusoidal representation networks to predict fMRI signals from EEG

no code implementations6 Nov 2023 Yamin Li, Ange Lou, Ziyuan Xu, Shiyu Wang, Catie Chang

The ability to obtain fMRI information from EEG would enable cost-effective, imaging across a wider set of brain regions.

EEG Feature Engineering

SAMSNeRF: Segment Anything Model (SAM) Guides Dynamic Surgical Scene Reconstruction by Neural Radiance Field (NeRF)

no code implementations22 Aug 2023 Ange Lou, Yamin Li, Xing Yao, Yike Zhang, Jack Noble

The accurate reconstruction of surgical scenes from surgical videos is critical for various applications, including intraoperative navigation and image-guided robotic surgery automation.

Depth Estimation Position

AFFIRM: Affinity Fusion-based Framework for Iteratively Random Motion correction of multi-slice fetal brain MRI

1 code implementation12 May 2022 Wen Shi, Haoan Xu, Cong Sun, Jiwei Sun, Yamin Li, Xinyi Xu, Tianshu Zheng, Yi Zhang, Guangbin Wang, Dan Wu

Multi-slice magnetic resonance images of the fetal brain are usually contaminated by severe and arbitrary fetal and maternal motion.

Super-Resolution

One Million Scenes for Autonomous Driving: ONCE Dataset

1 code implementation21 Jun 2021 Jiageng Mao, Minzhe Niu, Chenhan Jiang, Hanxue Liang, Jingheng Chen, Xiaodan Liang, Yamin Li, Chaoqiang Ye, Wei zhang, Zhenguo Li, Jie Yu, Hang Xu, Chunjing Xu

To facilitate future research on exploiting unlabeled data for 3D detection, we additionally provide a benchmark in which we reproduce and evaluate a variety of self-supervised and semi-supervised methods on the ONCE dataset.

3D Object Detection Autonomous Driving +1

Graph-Stega: Semantic Controllable Steganographic Text Generation Guided by Knowledge Graph

no code implementations2 Jun 2020 Zhongliang Yang, Baitao Gong, Yamin Li, Jinshuai Yang, Zhiwen Hu, Yongfeng Huang

On the one hand, we hide the secret information by coding the path in the knowledge graph, but not the conditional probability of each generated word; on the other hand, we can control the semantic expression of the generated steganographic text to a certain extent.

Text Generation

Probabilistic Radiomics: Ambiguous Diagnosis with Controllable Shape Analysis

no code implementations20 Oct 2019 Jiancheng Yang, Rongyao Fang, Bingbing Ni, Yamin Li, Yi Xu, Linguo Li

The final diagnosis is obtained by combining the ambiguity prior sample and lesion representation, and the whole network named $DenseSharp^{+}$ is end-to-end trainable.

Probabilistic Deep Learning

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