no code implementations • ECCV 2020 • Haixin Wang, Tianhao Zhang, Muzhi Yu, Jinan Sun, Wei Ye, Chen Wang , Shikun Zhang
Recently, stacked networks show powerful performance in Image Restoration, such as challenging motion deblurring problems.
1 code implementation • 16 Dec 2023 • Yihang Zhai, Haixin Wang, Jianlong Chang, Xinlong Yang, Jinan Sun, Shikun Zhang, Qi Tian
Instruction tuning has shown promising potential for developing general-purpose AI capabilities by using large-scale pre-trained models and boosts growing research to integrate multimodal information for creative applications.
no code implementations • 9 May 2023 • Chaoya Jiang, Rui Xie, Wei Ye, Jinan Sun, Shikun Zhang
Cross-modal contrastive learning in vision language pretraining (VLP) faces the challenge of (partial) false negatives.
no code implementations • 17 Mar 2023 • Haixin Wang, Jianlong Chang, Xiao Luo, Jinan Sun, Zhouchen Lin, Qi Tian
Despite recent competitive performance across a range of vision tasks, vision Transformers still have an issue of heavy computational costs.
no code implementations • ICCV 2023 • Xinlong Yang, Haixin Wang, Jinan Sun, Shikun Zhang, Chong Chen, Xian-Sheng Hua, Xiao Luo
This paper investigates a realistic but understudied problem of image retrieval under label noise, which could lead to severe overfitting or memorization of noisy samples during optimization.
no code implementations • 29 Dec 2021 • Tong Zhang, Wei Ye, Baosong Yang, Long Zhang, Xingzhang Ren, Dayiheng Liu, Jinan Sun, Shikun Zhang, Haibo Zhang, Wen Zhao
Inspired by the observation that low-frequency words form a more compact embedding space, we tackle this challenge from a representation learning perspective.
no code implementations • ACL 2021 • Tong Zhang, Long Zhang, Wei Ye, Bo Li, Jinan Sun, Xiaoyu Zhu, Wen Zhao, Shikun Zhang
This paper proposes a sophisticated neural architecture to incorporate bilingual dictionaries into Neural Machine Translation (NMT) models.
no code implementations • 21 Mar 2021 • Rui Xie, Wei Ye, Jinan Sun, Shikun Zhang
Code summaries are brief natural language descriptions of source code pieces.
no code implementations • 1 Jan 2021 • Yueheng Li, Tianhao Zhang, Chen Wang, Jinan Sun, Shikun Zhang, Guangming Xie
We explore energy-based solutions for cooperative multi-agent reinforcement learning (MARL) using the idea of function factorization in centralized training with decentralized execution (CTDE).
Multi-agent Reinforcement Learning reinforcement-learning +3
no code implementations • 19 Apr 2018 • Haixin Wang, Xingzhang Ren, Jinan Sun, Wei Ye, Long Chen, Muzhi Yu, Shikun Zhang
Specically, we propose to measure the quality of each leaf node of every decision tree in the random forest to determine hard examples.