Search Results for author: Nannan Li

Found 25 papers, 9 papers with code

Asymmetrical Siamese Network for Point Clouds Normal Estimation

no code implementations14 Jun 2024 Wei Jin, Jun Zhou, Nannan Li, Haba Madeline, Xiuping Liu

Evaluation of existing methods on this new dataset reveals their inability to adapt to different types of shapes, indicating a degree of overfitting.

Refining 3D Point Cloud Normal Estimation via Sample Selection

no code implementations20 May 2024 Jun Zhou, Yaoshun Li, Hongchen Tan, Mingjie Wang, Nannan Li, Xiuping Liu

In recent years, point cloud normal estimation, as a classical and foundational algorithm, has garnered extensive attention in the field of 3D geometric processing.

UniHuman: A Unified Model for Editing Human Images in the Wild

1 code implementation CVPR 2024 Nannan Li, Qing Liu, Krishna Kumar Singh, Yilin Wang, Jianming Zhang, Bryan A. Plummer, Zhe Lin

In this paper, we propose UniHuman, a unified model that addresses multiple facets of human image editing in real-world settings.

2k

Fine-grained Text and Image Guided Point Cloud Completion with CLIP Model

no code implementations17 Aug 2023 Wei Song, Jun Zhou, Mingjie Wang, Hongchen Tan, Nannan Li, Xiuping Liu

In this work, we propose a novel multimodal fusion network for point cloud completion, which can simultaneously fuse visual and textual information to predict the semantic and geometric characteristics of incomplete shapes effectively.

Language Modelling Point Cloud Completion

Leaf Cultivar Identification via Prototype-enhanced Learning

no code implementations5 May 2023 Yiyi Zhang, Zhiwen Ying, Ying Zheng, Cuiling Wu, Nannan Li, Jun Wang, Xianzhong Feng, Xiaogang Xu

Plant leaf identification is crucial for biodiversity protection and conservation and has gradually attracted the attention of academia in recent years.

Fine-Grained Image Classification

Supervised Attribute Information Removal and Reconstruction for Image Manipulation

1 code implementation13 Jul 2022 Nannan Li, Bryan A. Plummer

Thus, the source attribute information can often be hidden in the disentangled features, leading to unwanted image editing effects.

Attribute Image Manipulation +1

A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks

1 code implementation28 May 2022 Yu Pan, Zeyong Su, Ao Liu, Jingquan Wang, Nannan Li, Zenglin Xu

To address this problem, we propose a universal weight initialization paradigm, which generalizes Xavier and Kaiming methods and can be widely applicable to arbitrary TCNNs.

Tensor Decomposition

BViT: Broad Attention based Vision Transformer

1 code implementation13 Feb 2022 Nannan Li, Yaran Chen, Weifan Li, Zixiang Ding, Dongbin Zhao

In this paper, we propose the broad attention to improve the performance by incorporating the attention relationship of different layers for vision transformer, which is called BViT.

Image Classification Object Recognition

Stacked BNAS: Rethinking Broad Convolutional Neural Network for Neural Architecture Search

no code implementations15 Nov 2021 Zixiang Ding, Yaran Chen, Nannan Li, Dongbin Zhao, C. L. Philip Chen

Moreover, multi-scale feature fusion and knowledge embedding are proposed to improve the performance of BCNN with shallow topology.

Neural Architecture Search

ABCP: Automatic Block-wise and Channel-wise Network Pruning via Joint Search

1 code implementation8 Oct 2021 Jiaqi Li, Haoran Li, Yaran Chen, Zixiang Ding, Nannan Li, Mingjun Ma, Zicheng Duan, Dongbing Zhao

Compared with the traditional rule-based pruning method, this pipeline saves human labor and achieves a higher compression ratio with lower accuracy loss.

Network Pruning

Predicate correlation learning for scene graph generation

no code implementations6 Jul 2021 Leitian Tao, Li Mi, Nannan Li, Xianhang Cheng, Yaosi Hu, Zhenzhong Chen

For a typical Scene Graph Generation (SGG) method, there is often a large gap in the performance of the predicates' head classes and tail classes.

Graph Generation Scene Graph Generation

Heuristic Rank Selection with Progressively Searching Tensor Ring Network

no code implementations22 Sep 2020 Nannan Li, Yu Pan, Yaran Chen, Zixiang Ding, Dongbin Zhao, Zenglin Xu

Interestingly, we discover that part of the rank elements is sensitive and usually aggregate in a narrow region, namely an interest region.

BNAS-v2: Memory-efficient and Performance-collapse-prevented Broad Neural Architecture Search

no code implementations18 Sep 2020 Zixiang Ding, Yaran Chen, Nannan Li, Dongbin Zhao

For this consequent issue, two solutions are given: 1) we propose Confident Learning Rate (CLR) that considers the confidence of gradient for architecture weights update, increasing with the training time of over-parameterized BCNN; 2) we introduce the combination of partial channel connections and edge normalization that also can improve the memory efficiency further.

Neural Architecture Search

Towards Visual Distortion in Black-Box Attacks

1 code implementation21 Jul 2020 Nannan Li, Zhenzhong Chen

Constructing adversarial examples in a black-box threat model injures the original images by introducing visual distortion.

Perceptual Distance

Learning Compact Reward for Image Captioning

no code implementations24 Mar 2020 Nannan Li, Zhenzhong Chen

Adversarial learning has shown its advances in generating natural and diverse descriptions in image captioning.

Diversity Image Captioning +2

BNAS:An Efficient Neural Architecture Search Approach Using Broad Scalable Architecture

no code implementations18 Jan 2020 Zixiang Ding, Yaran Chen, Nannan Li, Dongbin Zhao, Zhiquan Sun, C. L. Philip Chen

In this paper, we propose Broad Neural Architecture Search (BNAS) where we elaborately design broad scalable architecture dubbed Broad Convolutional Neural Network (BCNN) to solve the above issue.

Neural Architecture Search reinforcement-learning +1

A Survey of Deep Reinforcement Learning in Video Games

no code implementations23 Dec 2019 Kun Shao, Zhentao Tang, Yuanheng Zhu, Nannan Li, Dongbin Zhao

In this paper, we survey the progress of DRL methods, including value-based, policy gradient, and model-based algorithms, and compare their main techniques and properties.

Real-Time Strategy Games reinforcement-learning +1

Non-rigid 3D shape retrieval based on multi-view metric learning

no code implementations20 Mar 2019 Haohao Li, Shengfa Wang, Nannan Li, Zhixun Su, Ximin Liu

The different intrinsic representations (features) focus on different geometric properties to describe the same 3D shape, which makes the representations are related.

3D Shape Classification 3D Shape Retrieval +3

BLP -- Boundary Likelihood Pinpointing Networks for Accurate Temporal Action Localization

no code implementations6 Nov 2018 Weijie Kong, Nannan Li, Shan Liu, Thomas Li, Ge Li

Despite tremendous progress achieved in temporal action detection, state-of-the-art methods still suffer from the sharp performance deterioration when localizing the starting and ending temporal action boundaries.

Action Detection regression +1

Step-by-step Erasion, One-by-one Collection: A Weakly Supervised Temporal Action Detector

no code implementations9 Jul 2018 Jia-Xing Zhong, Nannan Li, Weijie Kong, Tao Zhang, Thomas H. Li, Ge Li

Weakly supervised temporal action detection is a Herculean task in understanding untrimmed videos, since no supervisory signal except the video-level category label is available on training data.

Action Detection Temporal Localization

MRI Cross-Modality NeuroImage-to-NeuroImage Translation

no code implementations22 Jan 2018 Qianye Yang, Nannan Li, Zixu Zhao, Xingyu Fan, Eric I-Chao Chang, Yan Xu

Based on our proposed framework, we first propose a method for cross-modality registration by fusing the deformation fields to adopt the cross-modality information from translated modalities.

MRI segmentation Segmentation +1

A Self-Adaptive Proposal Model for Temporal Action Detection based on Reinforcement Learning

1 code implementation22 Jun 2017 Jingjia Huang, Nannan Li, Tao Zhang, Ge Li

Existing action detection algorithms usually generate action proposals through an extensive search over the video at multiple temporal scales, which brings about huge computational overhead and deviates from the human perception procedure.

Action Detection Position +2

Searching Action Proposals via Spatial Actionness Estimation and Temporal Path Inference and Tracking

no code implementations23 Aug 2016 Nannan Li, Dan Xu, Zhenqiang Ying, Zhihao LI, Ge Li

In this paper, we address the problem of searching action proposals in unconstrained video clips.

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