Search Results for author: Shijie Li

Found 20 papers, 8 papers with code

Hardware Phi-1.5B: A Large Language Model Encodes Hardware Domain Specific Knowledge

no code implementations27 Jan 2024 Weimin Fu, Shijie Li, Yifang Zhao, Haocheng Ma, Raj Dutta, Xuan Zhang, Kaichen Yang, Yier Jin, Xiaolong Guo

The creation of this first pretrained, hardware domain specific large language model marks a significant advancement, offering improved performance in hardware design and verification tasks and illustrating a promising path forward for AI applications in the semiconductor sector.

Language Modelling Large Language Model

VaLID: Variable-Length Input Diffusion for Novel View Synthesis

no code implementations14 Dec 2023 Shijie Li, Farhad G. Zanjani, Haitam Ben Yahia, Yuki M. Asano, Juergen Gall, Amirhossein Habibian

This is because the source-view images and corresponding poses are processed separately and injected into the model at different stages.

Image Generation Novel View Synthesis +1

Self-supervised OCT Image Denoising with Slice-to-Slice Registration and Reconstruction

1 code implementation26 Nov 2023 Shijie Li, Palaiologos Alexopoulos, Anse Vellappally, Ronald Zambrano, Wollstein Gadi, Guido Gerig

Strong speckle noise is inherent to optical coherence tomography (OCT) imaging and represents a significant obstacle for accurate quantitative analysis of retinal structures which is key for advances in clinical diagnosis and monitoring of disease.

Image Denoising Self-Supervised Learning

TFNet: Exploiting Temporal Cues for Fast and Accurate LiDAR Semantic Segmentation

no code implementations14 Sep 2023 Rong Li, Shijie Li, Xieyuanli Chen, Teli Ma, Juergen Gall, Junwei Liang

In this paper, we present TFNet, a range-image-based LiDAR semantic segmentation method that utilizes temporal information to address this issue.

Autonomous Driving LIDAR Semantic Segmentation +1

Semantic RGB-D Image Synthesis

no code implementations22 Aug 2023 Shijie Li, Rong Li, Juergen Gall

In this paper, we therefore propose a generator for multi-modal data that separates modal-independent information of the semantic layout from the modal-dependent information that is needed to generate an RGB and a depth image, respectively.

Image Generation Image Segmentation +2

Microscopy Image Segmentation via Point and Shape Regularized Data Synthesis

1 code implementation18 Aug 2023 Shijie Li, Mengwei Ren, Thomas Ach, Guido Gerig

Current deep learning-based approaches for the segmentation of microscopy images heavily rely on large amount of training data with dense annotation, which is highly costly and laborious in practice.

Image Segmentation Segmentation +1

Crop mapping in the small sample/no sample case: an approach using a two-level cascade classifier and integrating domain knowledge

no code implementations26 Dec 2022 Yunze Zang, Yifei Liu, Xuehong Chen, Anqi Li, Yichen Zhai, Shijie Li, Luling Liu, Chuanhai Zhu, Ruilin Chen, Shupeng Li, Na Jie

To solve this problem, a crop mapping method in the small sample/no sample case that integrating domain knowledge and using a cascaded classification framework that combine a weak classifier learned from samples with strong features and a strong classifier trained by samples with weak feature was proposed.

Management valid

Toward An Optimal Selection of Dialogue Strategies: A Target-Driven Approach for Intelligent Outbound Robots

no code implementations22 Jun 2022 Ruifeng Qian, Shijie Li, Mengjiao Bao, Huan Chen, Yu Che

With the growth of the economy and society, enterprises, especially in the FinTech industry, have increasing demands of outbound calls for customers such as debt collection, marketing, anti-fraud calls, and so on.


Spatial-Temporal Consistency Network for Low-Latency Trajectory Forecasting

no code implementations ICCV 2021 Shijie Li, Yanying Zhou, Jinhui Yi, Juergen Gall

Trajectory forecasting is a crucial step for autonomous vehicles and mobile robots in order to navigate and interact safely.

Autonomous Vehicles Navigate +1

Multi-scale Interaction for Real-time LiDAR Data Segmentation on an Embedded Platform

2 code implementations20 Aug 2020 Shijie Li, Xieyuanli Chen, Yun Liu, Dengxin Dai, Cyrill Stachniss, Juergen Gall

Real-time semantic segmentation of LiDAR data is crucial for autonomously driving vehicles, which are usually equipped with an embedded platform and have limited computational resources.

Autonomous Vehicles Real-Time 3D Semantic Segmentation +1

Rethinking 3D LiDAR Point Cloud Segmentation

1 code implementation10 Aug 2020 Shijie Li, Yun Liu, Juergen Gall

Many point-based semantic segmentation methods have been designed for indoor scenarios, but they struggle if they are applied to point clouds that are captured by a LiDAR sensor in an outdoor environment.

Autonomous Driving Decoder +3

MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation

1 code implementation16 Jun 2020 Shijie Li, Yazan Abu Farha, Yun Liu, Ming-Ming Cheng, Juergen Gall

Despite the capabilities of these approaches in capturing temporal dependencies, their predictions suffer from over-segmentation errors.

Action Segmentation Segmentation

MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation

1 code implementation21 Apr 2020 Yu Qiu, Yun Liu, Shijie Li, Jing Xu

On the other hand, fast training/testing and low computational cost are also necessary for quick deployment and development of COVID-19 screening systems, but traditional deep learning methods are usually computationally intensive.

Computational Efficiency COVID-19 Diagnosis +2

Exploring Frame Segmentation Networks for Temporal Action Localization

no code implementations14 Feb 2019 Ke Yang, Xiaolong Shen, Peng Qiao, Shijie Li, Dongsheng Li, Yong Dou

The proposed FSN can make dense predictions at frame-level for a video clip using both spatial and temporal context information.

Open-Ended Question Answering Temporal Action Localization

Joint Association Graph Screening and Decomposition for Large-scale Linear Dynamical Systems

no code implementations17 Nov 2014 Yiyuan She, Yuejia He, Shijie Li, Dapeng Wu

In particular, our method can pre-determine and remove unnecessary edges based on the joint graphical structure, referred to as JAG screening, and can decompose a large network into smaller subnetworks in a robust manner, referred to as JAG decomposition.

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