Search Results for author: Siyuan Li

Found 19 papers, 7 papers with code

Offline Reinforcement Learning with Reverse Model-based Imagination

no code implementations1 Oct 2021 Jianhao Wang, Wenzhe Li, Haozhe Jiang, Guangxiang Zhu, Siyuan Li, Chongjie Zhang

These reverse imaginations provide informed data augmentation for the model-free policy learning and enable conservative generalization beyond the offline dataset.

Data Augmentation Offline RL

Align Yourself: Self-supervised Pre-training for Fine-grained Recognition via Saliency Alignment

no code implementations30 Jun 2021 Di wu, Siyuan Li, Zelin Zang, Kai Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li

In this paper, we first point out that current contrastive methods are prone to memorizing background/foreground texture and therefore have a limitation in localizing the foreground object.

Contrastive Learning Image Classification +1

Active Hierarchical Exploration with Stable Subgoal Representation Learning

no code implementations31 May 2021 Siyuan Li, Jin Zhang, Jianhao Wang, Yang Yu, Chongjie Zhang

Although GCHRL possesses superior exploration ability by decomposing tasks via subgoals, existing GCHRL methods struggle in temporally extended tasks with sparse external rewards, since the high-level policy learning relies on external rewards.

Continuous Control Hierarchical Reinforcement Learning +1

Unsupervised Deep Manifold Attributed Graph Embedding

1 code implementation27 Apr 2021 Zelin Zang, Siyuan Li, Di wu, Jianzhu Guo, Yongjie Xu, Stan Z. Li

Unsupervised attributed graph representation learning is challenging since both structural and feature information are required to be represented in the latent space.

Graph Embedding Graph Representation Learning +2

Unveiling the Power of Mixup for Stronger Classifiers

no code implementations24 Mar 2021 Zicheng Liu, Siyuan Li, Di wu, ZhiYuan Chen, Lirong Wu, Jianzhu Guo, Stan Z. Li

Additionally, the optimization stability of mixup training is constantly troubled by the label mismatch.

Classification Data Augmentation +2

Towards Robust Graph Neural Networks against Label Noise

no code implementations1 Jan 2021 Jun Xia, Haitao Lin, Yongjie Xu, Lirong Wu, Zhangyang Gao, Siyuan Li, Stan Z. Li

A pseudo label is computed from the neighboring labels for each node in the training set using LP; meta learning is utilized to learn a proper aggregation of the original and pseudo label as the final label.

Learning with noisy labels Meta-Learning +1

Learning Subgoal Representations with Slow Dynamics

no code implementations ICLR 2021 Siyuan Li, Lulu Zheng, Jianhao Wang, Chongjie Zhang

In goal-conditioned Hierarchical Reinforcement Learning (HRL), a high-level policy periodically sets subgoals for a low-level policy, and the low-level policy is trained to reach those subgoals.

Continuous Control Hierarchical Reinforcement Learning +1

Invertible Manifold Learning for Dimension Reduction

1 code implementation7 Oct 2020 Siyuan Li, Haitao Lin, Zelin Zang, Lirong Wu, Jun Xia, Stan Z. Li

Dimension reduction (DR) aims to learn low-dimensional representations of high-dimensional data with the preservation of essential information.

Dimensionality Reduction

Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation

1 code implementation21 Sep 2020 Lirong Wu, Zicheng Liu, Zelin Zang, Jun Xia, Siyuan Li, Stan Z. Li

Though manifold-based clustering has become a popular research topic, we observe that one important factor has been omitted by these works, namely that the defined clustering loss may corrupt the local and global structure of the latent space.

Deep Clustering Representation Learning

Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals

no code implementations CVPR 2020 Siyuan Li, Semih Günel, Mirela Ostrek, Pavan Ramdya, Pascal Fua, Helge Rhodin

We compare our approach with existing domain transfer methods and demonstrate improved pose estimation accuracy on Drosophila melanogaster (fruit fly), Caenorhabditis elegans (worm) and Danio rerio (zebrafish), without requiring any manual annotation on the target domain and despite using simplistic off-the-shelf animal characters for simulation, or simple geometric shapes as models.

Pose Estimation Translation

Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards

1 code implementation NeurIPS 2019 Siyuan Li, Rui Wang, Minxue Tang, Chongjie Zhang

In addition, we also theoretically prove that optimizing low-level skills with this auxiliary reward will increase the task return for the joint policy.

Hierarchical Reinforcement Learning

Single Image Deraining: A Comprehensive Benchmark Analysis

1 code implementation CVPR 2019 Siyuan Li, Iago Breno Araujo, Wenqi Ren, Zhangyang Wang, Eric K. Tokuda, Roberto Hirata Junior, Roberto Cesar-Junior, Jiawan Zhang, Xiaojie Guo, Xiaochun Cao

We present a comprehensive study and evaluation of existing single image deraining algorithms, using a new large-scale benchmark consisting of both synthetic and real-world rainy images. This dataset highlights diverse data sources and image contents, and is divided into three subsets (rain streak, rain drop, rain and mist), each serving different training or evaluation purposes.

Single Image Deraining

PFLD: A Practical Facial Landmark Detector

14 code implementations28 Feb 2019 Xiaojie Guo, Siyuan Li, Jinke Yu, Jiawan Zhang, Jiayi Ma, Lin Ma, Wei Liu, Haibin Ling

Being accurate, efficient, and compact is essential to a facial landmark detector for practical use.

Face Alignment Facial Landmark Detection

Context-Aware Policy Reuse

no code implementations11 Jun 2018 Siyuan Li, Fangda Gu, Guangxiang Zhu, Chongjie Zhang

Transfer learning can greatly speed up reinforcement learning for a new task by leveraging policies of relevant tasks.

Transfer Learning

Fast Single Image Rain Removal via a Deep Decomposition-Composition Network

no code implementations8 Apr 2018 Siyuan LI, Wenqi Ren, Jiawan Zhang, Jinke Yu, Xiaojie Guo

Rain effect in images typically is annoying for many multimedia and computer vision tasks.

Rain Removal

Deep Eyes: Binocular Depth-from-Focus on Focal Stack Pairs

no code implementations29 Nov 2017 Xinqing Guo, Zhang Chen, Siyuan Li, Yang Yang, Jingyi Yu

We then construct three individual networks: a Focus-Net to extract depth from a single focal stack, a EDoF-Net to obtain the extended depth of field (EDoF) image from the focal stack, and a Stereo-Net to conduct stereo matching.

Stereo Matching Stereo Matching Hand

An Optimal Online Method of Selecting Source Policies for Reinforcement Learning

no code implementations24 Sep 2017 Siyuan Li, Chongjie Zhang

In this paper, we develop an optimal online method to select source policies for reinforcement learning.

Q-Learning Robot Navigation +1

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