Search Results for author: Kun Han

Found 23 papers, 8 papers with code

Orion-14B: Open-source Multilingual Large Language Models

1 code implementation20 Jan 2024 Du Chen, Yi Huang, Xiaopu Li, Yongqiang Li, Yongqiang Liu, Haihui Pan, Leichao Xu, Dacheng Zhang, Zhipeng Zhang, Kun Han

In this study, we introduce Orion-14B, a collection of multilingual large language models with 14 billion parameters.

Scheduling

CVTHead: One-shot Controllable Head Avatar with Vertex-feature Transformer

1 code implementation11 Nov 2023 Haoyu Ma, Tong Zhang, Shanlin Sun, Xiangyi Yan, Kun Han, Xiaohui Xie

Reconstructing personalized animatable head avatars has significant implications in the fields of AR/VR.

Neural Rendering

Light Field Diffusion for Single-View Novel View Synthesis

no code implementations20 Sep 2023 Yifeng Xiong, Haoyu Ma, Shanlin Sun, Kun Han, Hao Tang, Xiaohui Xie

Starting from the camera pose matrices, LFD transforms them into light field encoding, with the same shape as the reference image, to describe the direction of each ray.

Denoising Novel View Synthesis +1

Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation with Meta-Learning

1 code implementation31 Aug 2023 Yiming Zhang, Tianang Leng, Kun Han, Xiaohui Xie

In conclusion, we present a novel approach for rapid online adaptation in interactive image segmentation, adapting to a new organ in just 0. 83 minutes.

Few-Shot Learning Image Segmentation +3

On-the-Fly Guidance Training for Medical Image Registration

1 code implementation29 Aug 2023 Yicheng Chen, Shengxiang Ji, Yuelin Xin, Kun Han, Xiaohui Xie

OFG notably boosts the precision of existing image registration techniques while maintaining the speed of learning-based methods.

Image Registration Medical Image Registration

Hybrid-CSR: Coupling Explicit and Implicit Shape Representation for Cortical Surface Reconstruction

no code implementations23 Jul 2023 Shanlin Sun, Thanh-Tung Le, Chenyu You, Hao Tang, Kun Han, Haoyu Ma, Deying Kong, Xiangyi Yan, Xiaohui Xie

We present Hybrid-CSR, a geometric deep-learning model that combines explicit and implicit shape representations for cortical surface reconstruction.

Surface Reconstruction

Hybrid Neural Diffeomorphic Flow for Shape Representation and Generation via Triplane

no code implementations4 Jul 2023 Kun Han, Shanlin Sun, Xiaohui Xie

Deep Implicit Functions (DIFs) have gained popularity in 3D computer vision due to their compactness and continuous representation capabilities.

3D Shape Generation 3D Shape Representation +1

Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction

no code implementations27 May 2023 Tung Le, Khai Nguyen, Shanlin Sun, Kun Han, Nhat Ho, Xiaohui Xie

The metric is defined by sliced Wasserstein distance on meshes represented as probability measures that generalize the set-based approach.

Surface Reconstruction

MedGen3D: A Deep Generative Framework for Paired 3D Image and Mask Generation

no code implementations8 Apr 2023 Kun Han, Yifeng Xiong, Chenyu You, Pooya Khosravi, Shanlin Sun, Xiangyi Yan, James Duncan, Xiaohui Xie

Then, we use an image sequence generator and semantic diffusion refiner conditioned on the generated mask sequences to produce realistic 3D medical images that align with the generated masks.

Image Segmentation Medical Image Segmentation +2

Localized Region Contrast for Enhancing Self-Supervised Learning in Medical Image Segmentation

no code implementations6 Apr 2023 Xiangyi Yan, Junayed Naushad, Chenyu You, Hao Tang, Shanlin Sun, Kun Han, Haoyu Ma, James Duncan, Xiaohui Xie

In this paper, we propose a novel contrastive learning framework that integrates Localized Region Contrast (LRC) to enhance existing self-supervised pre-training methods for medical image segmentation.

Contrastive Learning Image Segmentation +5

Identity-Aware Hand Mesh Estimation and Personalization from RGB Images

1 code implementation22 Sep 2022 Deying Kong, Linguang Zhang, Liangjian Chen, Haoyu Ma, Xiangyi Yan, Shanlin Sun, Xingwei Liu, Kun Han, Xiaohui Xie

In this paper, we propose an identity-aware hand mesh estimation model, which can incorporate the identity information represented by the intrinsic shape parameters of the subject.

Medical Image Registration via Neural Fields

no code implementations7 Jun 2022 Shanlin Sun, Kun Han, Hao Tang, Deying Kong, Junayed Naushad, Xiangyi Yan, Xiaohui Xie

Traditional methods for image registration are primarily optimization-driven, finding the optimal deformations that maximize the similarity between two images.

Image Registration Medical Image Registration +1

Topology-Preserving Shape Reconstruction and Registration via Neural Diffeomorphic Flow

1 code implementation CVPR 2022 Shanlin Sun, Kun Han, Deying Kong, Hao Tang, Xiangyi Yan, Xiaohui Xie

Recently DIFs-based methods have been proposed to handle shape reconstruction and dense point correspondences simultaneously, capturing semantic relationships across shapes of the same class by learning a DIFs-modeled shape template.

Organ Segmentation Template Matching

Diffeomorphic Image Registration with Neural Velocity Field

no code implementations25 Feb 2022 Kun Han, Shanlin Sun, Xiangyi Yan, Chenyu You, Hao Tang, Junayed Naushad, Haoyu Ma, Deying Kong, Xiaohui Xie

Here we propose a new optimization-based method named DNVF (Diffeomorphic Image Registration with Neural Velocity Field) which utilizes deep neural network to model the space of admissible transformations.

Image Registration

A Hybrid Task-Oriented Dialog System with Domain and Task Adaptive Pretraining

no code implementations8 Feb 2021 Boliang Zhang, Ying Lyu, Ning Ding, Tianhao Shen, Zhaoyang Jia, Kun Han, Kevin Knight

This paper describes our submission for the End-to-end Multi-domain Task Completion Dialog shared task at the 9th Dialog System Technology Challenge (DSTC-9).

dialog state tracking Natural Language Understanding +1

Spatial Context-Aware Self-Attention Model For Multi-Organ Segmentation

no code implementations16 Dec 2020 Hao Tang, Xingwei Liu, Kun Han, Shanlin Sun, Narisu Bai, Xuming Chen, Huang Qian, Yong liu, Xiaohui Xie

State-of-the-art CNN segmentation models apply either 2D or 3D convolutions on input images, with pros and cons associated with each method: 2D convolution is fast, less memory-intensive but inadequate for extracting 3D contextual information from volumetric images, while the opposite is true for 3D convolution.

Image Segmentation Organ Segmentation +2

DiDiSpeech: A Large Scale Mandarin Speech Corpus

no code implementations19 Oct 2020 Tingwei Guo, Cheng Wen, Dongwei Jiang, Ne Luo, Ruixiong Zhang, Shuaijiang Zhao, Wubo Li, Cheng Gong, Wei Zou, Kun Han, Xiangang Li

This paper introduces a new open-sourced Mandarin speech corpus, called DiDiSpeech.

Audio and Speech Processing

Learning Syntactic and Dynamic Selective Encoding for Document Summarization

no code implementations25 Mar 2020 Haiyang Xu, Yahao He, Kun Han, Junwen Chen, Xiangang Li

Our approach has the following contributions: first, we incorporate syntactic information such as constituency parsing trees into the encoding sequence to learn both the semantic and syntactic information from the document, resulting in more accurate summary; second, we propose a dynamic gate network to select the salient information based on the context of the decoder state, which is essential to document summarization.

Constituency Parsing Document Summarization

Adversarial Multi-Binary Neural Network for Multi-class Classification

no code implementations25 Mar 2020 Haiyang Xu, Junwen Chen, Kun Han, Xiangang Li

Multi-class text classification is one of the key problems in machine learning and natural language processing.

General Classification Multi-class Classification +3

Selective Attention Encoders by Syntactic Graph Convolutional Networks for Document Summarization

no code implementations18 Mar 2020 Haiyang Xu, Yun Wang, Kun Han, Baochang Ma, Junwen Chen, Xiangang Li

Abstractive text summarization is a challenging task, and one need to design a mechanism to effectively extract salient information from the source text and then generate a summary.

Abstractive Text Summarization Document Summarization

Learning Alignment for Multimodal Emotion Recognition from Speech

1 code implementation6 Sep 2019 Haiyang Xu, HUI ZHANG, Kun Han, Yun Wang, Yiping Peng, Xiangang Li

Further, emotion recognition will be beneficial from using audio-textual multimodal information, it is not trivial to build a system to learn from multimodality.

Multimodal Emotion Recognition Speech Emotion Recognition +2

Using Context Information for Dialog Act Classification in DNN Framework

no code implementations EMNLP 2017 Yang Liu, Kun Han, Zhao Tan, Yun Lei

Previous work on dialog act (DA) classification has investigated different methods, such as hidden Markov models, maximum entropy, conditional random fields, graphical models, and support vector machines.

Classification Dialog Act Classification +3

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