Search Results for author: Shanshan Zhao

Found 21 papers, 8 papers with code

Domain Re-Modulation for Few-Shot Generative Domain Adaptation

no code implementations6 Feb 2023 Yi Wu, Ziqiang Li, Chaoyue Wang, Heliang Zheng, Shanshan Zhao, Bin Li, DaCheng Tao

This allows for high-fidelity multi-domain and hybrid-domain generation by integrating multiple M&A modules in a single generator.

Association Domain Adaptation

Adaptive Edge-to-Edge Interaction Learning for Point Cloud Analysis

no code implementations20 Nov 2022 Shanshan Zhao, Mingming Gong, Xi Li, DaCheng Tao

To explore the role of the relation between edges, this paper proposes a novel Adaptive Edge-to-Edge Interaction Learning module, which aims to enhance the point-to-point relation through modelling the edge-to-edge interaction in the local region adaptively.

Semantic Segmentation

DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting

1 code implementation19 Nov 2022 Maoyuan Ye, Jing Zhang, Shanshan Zhao, Juhua Liu, Tongliang Liu, Bo Du, DaCheng Tao

In this paper, we present DeepSolo, a simple DETR-like baseline that lets a single Decoder with Explicit Points Solo for text detection and recognition simultaneously.

Scene Text Detection Text Matching +1

MetaComp: Learning to Adapt for Online Depth Completion

no code implementations21 Jul 2022 Yang Chen, Shanshan Zhao, Wei Ji, Mingming Gong, Liping Xie

However, facing a new environment where the test data occurs online and differs from the training data in the RGB image content and depth sparsity, the trained model might suffer severe performance drop.

Depth Completion Meta-Learning +1

MeshMAE: Masked Autoencoders for 3D Mesh Data Analysis

no code implementations20 Jul 2022 Yaqian Liang, Shanshan Zhao, Baosheng Yu, Jing Zhang, Fazhi He

We first randomly mask some patches of the mesh and feed the corrupted mesh into Mesh Transformers.

DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer

2 code implementations10 Jul 2022 Maoyuan Ye, Jing Zhang, Shanshan Zhao, Juhua Liu, Bo Du, DaCheng Tao

However, these methods built upon detection transformer framework might achieve sub-optimal training efficiency and performance due to coarse positional query modeling. In addition, the point label form exploited in previous works implies the reading order of humans, which impedes the detection robustness from our observation.

Inductive Bias Scene Text Detection

Recent Advances for Quantum Neural Networks in Generative Learning

no code implementations7 Jun 2022 Jinkai Tian, Xiaoyu Sun, Yuxuan Du, Shanshan Zhao, Qing Liu, Kaining Zhang, Wei Yi, Wanrong Huang, Chaoyue Wang, Xingyao Wu, Min-Hsiu Hsieh, Tongliang Liu, Wenjing Yang, DaCheng Tao

Due to the intrinsic probabilistic nature of quantum mechanics, it is reasonable to postulate that quantum generative learning models (QGLMs) may surpass their classical counterparts.

BIG-bench Machine Learning Quantum Machine Learning

Iterative Geometry-Aware Cross Guidance Network for Stereo Image Inpainting

no code implementations8 May 2022 Ang Li, Shanshan Zhao, Qingjie Zhang, Qiuhong Ke

The IGGNet contains two key ingredients, i. e., a Geometry-Aware Attention (GAA) module and an Iterative Cross Guidance (ICG) strategy.

Image Inpainting

FIBA: Frequency-Injection based Backdoor Attack in Medical Image Analysis

1 code implementation CVPR 2022 Yu Feng, Benteng Ma, Jing Zhang, Shanshan Zhao, Yong Xia, DaCheng Tao

However, designing a unified BA method that can be applied to various MIA systems is challenging due to the diversity of imaging modalities (e. g., X-Ray, CT, and MRI) and analysis tasks (e. g., classification, detection, and segmentation).

Backdoor Attack Classification +4

Domain Generalization via Entropy Regularization

1 code implementation NeurIPS 2020 Shanshan Zhao, Mingming Gong, Tongliang Liu, Huan Fu, DaCheng Tao

To arrive at this, some methods introduce a domain discriminator through adversarial learning to match the feature distributions in multiple source domains.

Domain Generalization

Adaptive Context-Aware Multi-Modal Network for Depth Completion

1 code implementation25 Aug 2020 Shanshan Zhao, Mingming Gong, Huan Fu, DaCheng Tao

Furthermore, considering the mutli-modality of input data, we exploit the graph propagation on the two modalities respectively to extract multi-modal representations.

Depth Completion

Group-wise Deep Co-saliency Detection

no code implementations24 Jul 2017 Lina Wei, Shanshan Zhao, Omar El Farouk Bourahla, Xi Li, Fei Wu

In this paper, we propose an end-to-end group-wise deep co-saliency detection approach to address the co-salient object discovery problem based on the fully convolutional network (FCN) with group input and group output.

Co-Salient Object Detection Object Discovery +1

Deep Optical Flow Estimation Via Multi-Scale Correspondence Structure Learning

no code implementations23 Jul 2017 Shanshan Zhao, Xi Li, Omar El Farouk Bourahla

Therefore, a key issue to solve in this area is how to effectively model the multi-scale correspondence structure properties in an adaptive end-to-end learning fashion.

Optical Flow Estimation

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