Search Results for author: Qing Lin

Found 7 papers, 0 papers with code

Make Me Happier: Evoking Emotions Through Image Diffusion Models

no code implementations13 Mar 2024 Qing Lin, Jingfeng Zhang, Yew Soon Ong, Mengmi Zhang

For the first time, we present a novel challenge of emotion-evoked image generation, aiming to synthesize images that evoke target emotions while retaining the semantics and structures of the original scenes.

Image Generation

Multi-Modality Deep Network for JPEG Artifacts Reduction

no code implementations4 May 2023 Xuhao Jiang, Weimin Tan, Qing Lin, Chenxi Ma, Bo Yan, Liquan Shen

In recent years, many convolutional neural network-based models are designed for JPEG artifacts reduction, and have achieved notable progress.

Contrastive Learning Image Compression +1

Rethinking Super-Resolution as Text-Guided Details Generation

no code implementations14 Jul 2022 Chenxi Ma, Bo Yan, Qing Lin, Weimin Tan, Siming Chen

To enhance the semantic accuracy and the visual quality of the reconstructed image, we explore the multi-modal fusion learning in SISR by proposing a Text-Guided Super-Resolution (TGSR) framework, which can effectively utilize the information from the text and image modalities.

Image Super-Resolution

Ensemble Making Few-Shot Learning Stronger

no code implementations12 May 2021 Qing Lin, Yongbin Liu, Wen Wen, Zhihua Tao

It is difficult for a single model to adapt to various relation learning, which results in the high variance problem.

Few-Shot Learning Relation +1

Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers

no code implementations6 Jul 2020 Dae Heun Koh, Pierre Côte de Soux, Laura Dominé, François Drielsma, Ran Itay, Qing Lin, Kazuhiro Terao, Ka Vang Tsang, Tracy Usher

This work contributes to the development of an end-to-end optimizable full data reconstruction chain for LArTPCs, in particular pixel-based 3D imaging detectors including the near detector of the Deep Underground Neutrino Experiment.

Clustering Instance Segmentation +1

Clustering of Electromagnetic Showers and Particle Interactions with Graph Neural Networks in Liquid Argon Time Projection Chambers Data

no code implementations2 Jul 2020 Francois Drielsma, Qing Lin, Pierre Côte de Soux, Laura Dominé, Ran Itay, Dae Heun Koh, Bradley J. Nelson, Kazuhiro Terao, Ka Vang Tsang, Tracy L. Usher

The optimized algorithm is then applied to the related task of clustering particle instances into interactions and yields a mean ARI of 99. 2 % for an interaction density of $\sim\mathcal{O}(1)\, m^{-3}$.

Clustering

Point Proposal Network for Reconstructing 3D Particle Endpoints with Sub-Pixel Precision in Liquid Argon Time Projection Chambers

no code implementations26 Jun 2020 Laura Dominé, Pierre Côte de Soux, François Drielsma, Dae Heun Koh, Ran Itay, Qing Lin, Kazuhiro Terao, Ka Vang Tsang, Tracy L. Usher

Using as a benchmark the PILArNet public LArTPC data sample in which the voxel resolution is 3mm/voxel, our algorithm successfully predicted 96. 8% and 97. 8% of 3D points within a distance of 3 and 10~voxels from the provided true point locations respectively.

Clustering

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