1 code implementation • 17 Feb 2023 • Zhijie Jia, Lin Chen, Kaiwen Hu, Lechao Cheng, Zunlei Feng, Mingli Song
Despite the remarkable progress in semantic segmentation tasks with the advancement of deep neural networks, existing U-shaped hierarchical typical segmentation networks still suffer from local misclassification of categories and inaccurate target boundaries.
1 code implementation • 14 Feb 2023 • Tian Qiu, Linyun Zhou, Wenxiang Xu, Lechao Cheng, Zunlei Feng, Mingli Song
Recent proposed DETR variants have made tremendous progress in various scenarios due to their streamlined processes and remarkable performance.
no code implementations • 14 Jan 2023 • Zipeng Zhong, Jie Song, Zunlei Feng, Tiantao Liu, Lingxiang Jia, Shaolun Yao, Tingjun Hou, Mingli Song
Afterwards, we analyze these methods in terms of their mechanism and performance, and introduce popular evaluation metrics for them, in which we also provide a detailed comparison among representative methods on several public datasets.
1 code implementation • 30 Nov 2022 • Siqi Fan, Fenghua Zhu, Zunlei Feng, Yisheng Lv, Mingli Song, Fei-Yue Wang
Pseudo supervision is regarded as the core idea in semi-supervised learning for semantic segmentation, and there is always a tradeoff between utilizing only the high-quality pseudo labels and leveraging all the pseudo labels.
no code implementations • 29 Nov 2022 • Huiyan Qi, Lechao Cheng, Jingjing Chen, Yue Yu, Xue Song, Zunlei Feng, Yu-Gang Jiang
Transfer learning aims to improve the performance of target tasks by transferring knowledge acquired in source tasks.
1 code implementation • 23 Nov 2022 • Shunyu Liu, Yihe Zhou, Jie Song, Tongya Zheng, KaiXuan Chen, Tongtian Zhu, Zunlei Feng, Mingli Song
Value Decomposition (VD) aims to deduce the contributions of agents for decentralized policies in the presence of only global rewards, and has recently emerged as a powerful credit assignment paradigm for tackling cooperative Multi-Agent Reinforcement Learning (MARL) problems.
no code implementations • 27 Jul 2022 • Donglin Xie, Ruonan Yu, Gongfan Fang, Jie Song, Zunlei Feng, Xinchao Wang, Li Sun, Mingli Song
The goal of FedSA is to train a student model for a new task with the help of several decentralized teachers, whose pre-training tasks and data are different and agnostic.
1 code implementation • 27 Jul 2022 • Jie Lei, Zhao Liu, Zeyu Zou, Tong Li, Xu Juan, Shuaiwei Wang, Guoyu Yang, Zunlei Feng
On the other hand, GUS is introduced to suppress the feature ambiguity in the representation space.
1 code implementation • 8 Jul 2022 • Shunyu Liu, Jie Song, Yihe Zhou, Na Yu, KaiXuan Chen, Zunlei Feng, Mingli Song
In this work, we introduce a novel interactiOn Pattern disenTangling (OPT) method, to disentangle not only the joint value function into agent-wise value functions for decentralized execution, but also the entity interactions into interaction prototypes, each of which represents an underlying interaction pattern within a subgroup of the entities.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 5 Jul 2022 • Shunyu Liu, Na Yu, Jie Song, KaiXuan Chen, Zunlei Feng, Mingli Song
Despite the promising results achieved, state-of-the-art interactive reinforcement learning schemes rely on passively receiving supervision signals from advisor experts, in the form of either continuous monitoring or pre-defined rules, which inevitably result in a cumbersome and expensive learning process.
1 code implementation • 12 May 2022 • KaiXuan Chen, Shunyu Liu, Na Yu, Rong Yan, Quan Zhang, Jie Song, Zunlei Feng, Mingli Song
As the topology of the power system is in the form of graph structure, graph neural network based representation learning is naturally suitable for learning the status of the power system.
1 code implementation • 7 May 2022 • Zunlei Feng, Tian Qiu, Sai Wu, Xiaotuan Jin, Zengliang He, Mingli Song, Huiqiong Wang
In this paper, we attempt to build a generalizable framework that emulates the humans' recognition mechanism in the image classification task, hoping to improve the classification performance on unseen categories with the support of annotations of other categories.
no code implementations • 25 Mar 2022 • Jiacong Hu, Jing Gao, Zunlei Feng, Lechao Cheng, Jie Lei, Hujun Bao, Mingli Song
the feature maps are adopted to locate the critical features in each layer.
1 code implementation • 22 Mar 2022 • Zipeng Zhong, Jie Song, Zunlei Feng, Tiantao Liu, Lingxiang Jia, Shaolun Yao, Min Wu, Tingjun Hou, Mingli Song
Chemical reaction prediction, involving forward synthesis and retrosynthesis prediction, is a fundamental problem in organic synthesis.
no code implementations • 7 Mar 2022 • Haofei Zhang, Feng Mao, Mengqi Xue, Gongfan Fang, Zunlei Feng, Jie Song, Mingli Song
Moreover, the transformer-based students excel in learning amalgamated knowledge, as they have mastered heterogeneous detection tasks rapidly and achieved superior or at least comparable performance to those of the teachers in their specializations.
no code implementations • 16 Dec 2021 • Gengshi Han, Shunyu Liu, KaiXuan Chen, Na Yu, Zunlei Feng, Mingli Song
This paper proposes a controllable sample generation framework based on Conditional Tabular Generative Adversarial Network (CTGAN) to generate specified transient stability samples.
1 code implementation • 9 Dec 2021 • Zunlei Feng, Jiacong Hu, Sai Wu, Xiaotian Yu, Jie Song, Mingli Song
The aggregate gradient strategy is a versatile module for mainstream CNN classifiers.
1 code implementation • 23 Nov 2021 • Tongya Zheng, Zunlei Feng, Yu Wang, Chengchao Shen, Mingli Song, Xingen Wang, Xinyu Wang, Chun Chen, Hao Xu
Our proposed Dynamic Preference Structure (DPS) framework consists of two stages: structure sampling and graph fusion.
1 code implementation • 29 Sep 2021 • KaiXuan Chen, Jie Song, Shunyu Liu, Na Yu, Zunlei Feng, Gengshi Han, Mingli Song
A DKEPool network de facto disassembles representation learning into two stages, structure learning and distribution learning.
no code implementations • 1 Aug 2021 • Lechao Cheng, Zunlei Feng, Xinchao Wang, Ya Jie Liu, Jie Lei, Mingli Song
In this paper, we introduce a novel Reference semantic segmentation Network (Ref-Net) to conduct visual boundary knowledge translation.
1 code implementation • 1 Aug 2021 • Zunlei Feng, Lechao Cheng, Xinchao Wang, Xiang Wang, Yajie Liu, Xiangtong Du, Mingli Song
To this end, we propose a Translation Segmentation Network (Trans-Net), which comprises a segmentation network and two boundary discriminators.
1 code implementation • 1 Aug 2021 • Zunlei Feng, Zhonghua Wang, Xinchao Wang, Xiuming Zhang, Lechao Cheng, Jie Lei, Yuexuan Wang, Mingli Song
The diagnosis of MVI needs discovering the vessels that contain hepatocellular carcinoma cells and counting their number in each vessel, which depends heavily on experiences of the doctor, is largely subjective and time-consuming.
no code implementations • 28 Jul 2021 • Xin Gao, Zhenjiang Liu, Zunlei Feng, Chengji Shen, Kairi Ou, Haihong Tang, Mingli Song
Existing 2D image-based virtual try-on methods aim to transfer a target clothing image onto a reference person, which has two main disadvantages: cannot control the size and length precisely; unable to accurately estimate the user's figure in the case of users wearing thick clothes, resulting in inaccurate dressing effect.
no code implementations • ICCV 2021 • Zunlei Feng, Zhonghua Wang, Xinchao Wang, Yining Mao, Thomas Li, Jie Lei, Yuexuan Wang, Mingli Song
The existing two unsupervised methods are prone to failure on degenerated samples.
no code implementations • NeurIPS 2020 • Zunlei Feng, Yongming He, Xinchao Wang, Xin Gao, Jie Lei, Cheng Jin, Mingli Song
In this paper, we introduce the One-sample Guided Object Representation Disassembling (One-GORD) method, which only requires one annotated sample for each object category to learn disassembled object representation from unannotated images.
1 code implementation • 17 Oct 2020 • Shuai Xie, Zunlei Feng, Ying Chen, Songtao Sun, Chao Ma, Mingli Song
To deal with this problem, we propose a semantic Difficulty-awarE Active Learning (DEAL) network composed of two branches: the common segmentation branch and the semantic difficulty branch.
1 code implementation • NeurIPS 2020 • Yiding Yang, Zunlei Feng, Mingli Song, Xinchao Wang
In this paper, we introduce a novel graph convolutional network (GCN), termed as factorizable graph convolutional network(FactorGCN), that explicitly disentangles such intertwined relations encoded in a graph.
Ranked #3 on Node Classification on PATTERN 100k
no code implementations • 20 Aug 2020 • Xinhui Song, Tianyang Shi, Zunlei Feng, Mingli Song, Jackie Lin, Chuan-Jie Lin, Changjie Fan, Yi Yuan
Facial action unit (AU) intensity is an index to describe all visually discernible facial movements.
no code implementations • 13 Apr 2020 • Xinhui Song, Tianyang Shi, Tianjia Shao, Yi Yuan, Zunlei Feng, Changjie Fan
The generator learns to "render" a face image from a set of facial parameters in a differentiable way, and the feature extractor extracts deep features for measuring the similarity of the rendered image and input real image.
no code implementations • 3 Apr 2020 • Zunlei Feng, Xinchao Wang, Yongming He, Yike Yuan, Xin Gao, Mingli Song
In this paper, we study a new representation-learning task, which we termed as disassembling object representations.
no code implementations • 18 Dec 2019 • Da Chen, Yong-Liang Yang, Zunlei Feng, Xiang Wu, Mingli Song, Wenbin Li, Yuan He, Hui Xue, Feng Mao
This strategy leads to severe meta shift issues across multiple tasks, meaning the learned prototypes or class descriptors are not stable as each task only involves their own support set.
no code implementations • 13 Jun 2018 • Zunlei Feng, Zhenyun Yu, Yezhou Yang, Yongcheng Jing, Junxiao Jiang, Mingli Song
In the supervised attributes module, multiple attributes labels are adopted to ensure that different parts of the overall embedding correspond to different attributes.
1 code implementation • NeurIPS 2018 • Zunlei Feng, Xinchao Wang, Chenglong Ke, An-Xiang Zeng, DaCheng Tao, Mingli Song
To achieve disentangling using the labeled pairs, we follow a "encoding-swap-decoding" process, where we first swap the parts of their encodings corresponding to the shared attribute and then decode the obtained hybrid codes to reconstruct the original input pairs.
1 code implementation • ECCV 2018 • Yongcheng Jing, Yang Liu, Yezhou Yang, Zunlei Feng, Yizhou Yu, DaCheng Tao, Mingli Song
In this paper, we present a stroke controllable style transfer network that can achieve continuous and spatial stroke size control.
8 code implementations • 11 May 2017 • Yongcheng Jing, Yezhou Yang, Zunlei Feng, Jingwen Ye, Yizhou Yu, Mingli Song
We first propose a taxonomy of current algorithms in the field of NST.