1 code implementation • 17 Feb 2024 • Shanshan Zhong, Zhongzhan Huang, Daifeng Li, Wushao Wen, Jinghui Qin, Liang Lin
This strategy can implicitly enhance the model's robustness during the optimization process, mitigating instability risks arising from multimodal information inputs.
1 code implementation • 5 Dec 2023 • Shanshan Zhong, Zhongzhan Huang, ShangHua Gao, Wushao Wen, Liang Lin, Marinka Zitnik, Pan Zhou
To this end, we study LLMs on the popular Oogiri game which needs participants to have good creativity and strong associative thinking for responding unexpectedly and humorously to the given image, text, or both, and thus is suitable for LoT study.
1 code implementation • 9 May 2023 • Shanshan Zhong, Wushao Wen, Jinghui Qin, Qiangpu Chen, Zhongzhan Huang
In computer vision, the performance of deep neural networks (DNNs) is highly related to the feature extraction ability, i. e., the ability to recognize and focus on key pixel regions in an image.
1 code implementation • 9 May 2023 • Shanshan Zhong, Zhongzhan Huang, Wushao Wen, Jinghui Qin, Liang Lin
Our approach can make text-to-image diffusion models easier to use with better user experience, which demonstrates our approach has the potential for further advancing the development of user-friendly text-to-image generation models by bridging the semantic gap between simple narrative prompts and complex keyword-based prompts.
no code implementations • 13 Apr 2023 • Shanshan Zhong, Zhongzhan Huang, Wushao Wen, Jinghui Qin, Liang Lin
This technique enables the mitigation of the extra costs for performance improvement during training, such as parameter size and inference time, through these transformations during inference, and therefore SRP has great potential for industrial and practical applications.
no code implementations • 27 Oct 2022 • Shanshan Zhong, Wushao Wen, Jinghui Qin, Zhongzhan Huang
More and more empirical and theoretical evidence shows that deepening neural networks can effectively improve their performance under suitable training settings.
1 code implementation • 13 Sep 2022 • Shanshan Zhong, Wushao Wen, Jinghui Qin
Attention mechanism has gained great success in vision recognition.
1 code implementation • 22 Aug 2022 • Shanshan Zhong, Wushao Wen, Jinghui Qin
Recently many effective attention modules are proposed to boot the model performance by exploiting the internal information of convolutional neural networks in computer vision.
1 code implementation • 11 Apr 2019 • Jinghui Qin, Ziwei Xie, Yukai Shi, Wushao Wen
To identify whether a region is easy or hard, we propose a novel image difficulty recognition network based on PSNR prior.
no code implementations • 3 Oct 2018 • Andrey Ignatov, Radu Timofte, Thang Van Vu, Tung Minh Luu, Trung X. Pham, Cao Van Nguyen, Yongwoo Kim, Jae-Seok Choi, Munchurl Kim, Jie Huang, Jiewen Ran, Chen Xing, Xingguang Zhou, Pengfei Zhu, Mingrui Geng, Yawei Li, Eirikur Agustsson, Shuhang Gu, Luc van Gool, Etienne de Stoutz, Nikolay Kobyshev, Kehui Nie, Yan Zhao, Gen Li, Tong Tong, Qinquan Gao, Liu Hanwen, Pablo Navarrete Michelini, Zhu Dan, Hu Fengshuo, Zheng Hui, Xiumei Wang, Lirui Deng, Rang Meng, Jinghui Qin, Yukai Shi, Wushao Wen, Liang Lin, Ruicheng Feng, Shixiang Wu, Chao Dong, Yu Qiao, Subeesh Vasu, Nimisha Thekke Madam, Praveen Kandula, A. N. Rajagopalan, Jie Liu, Cheolkon Jung
This paper reviews the first challenge on efficient perceptual image enhancement with the focus on deploying deep learning models on smartphones.