Search Results for author: Siyuan Zhou

Found 15 papers, 6 papers with code

Video Object of Interest Segmentation

no code implementations6 Dec 2022 Siyuan Zhou, Chunru Zhan, Biao Wang, Tiezheng Ge, Yuning Jiang, Li Niu

Given a video and a target image of interest, our objective is to simultaneously segment and track all objects in the video that are relevant to the target image.

Semantic Segmentation Video Object Segmentation +1

Weak-shot Semantic Segmentation via Dual Similarity Transfer

1 code implementation5 Oct 2022 Junjie Chen, Li Niu, Siyuan Zhou, Jianlou Si, Chen Qian, Liqing Zhang

Proposal segmentation allows proposal-pixel similarity transfer from base classes to novel classes, which enables the mask learning of novel classes.

Semantic Segmentation Semantic Similarity +1

Learning Object Placement via Dual-path Graph Completion

1 code implementation23 Jul 2022 Siyuan Zhou, Liu Liu, Li Niu, Liqing Zhang

Object placement aims to place a foreground object over a background image with a suitable location and size.

Native Chinese Reader: A Dataset Towards Native-Level Chinese Machine Reading Comprehension

no code implementations13 Dec 2021 Shusheng Xu, Yichen Liu, Xiaoyu Yi, Siyuan Zhou, Huizi Li, Yi Wu

We present Native Chinese Reader (NCR), a new machine reading comprehension (MRC) dataset with particularly long articles in both modern and classical Chinese.

Common Sense Reasoning Machine Reading Comprehension

Weak-shot Semantic Segmentation by Transferring Semantic Affinity and Boundary

no code implementations4 Oct 2021 Siyuan Zhou, Li Niu, Jianlou Si, Chen Qian, Liqing Zhang

As a result, we find that pixel-level annotation of base categories can facilitate affinity learning and propagation, leading to higher-quality CAMs of novel categories.

Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation

Inducing Reusable Skills From Demonstrations with Option-Controller Network

no code implementations29 Sep 2021 Siyuan Zhou, Yikang Shen, Yuchen Lu, Aaron Courville, Joshua B. Tenenbaum, Chuang Gan

With the isolation of information and the synchronous calling mechanism, we can impose a division of works between the controller and options in an end-to-end training regime.

PlasticineLab: A Soft-Body Manipulation Benchmark with Differentiable Physics

1 code implementation ICLR 2021 Zhiao Huang, Yuanming Hu, Tao Du, Siyuan Zhou, Hao Su, Joshua B. Tenenbaum, Chuang Gan

Experimental results suggest that 1) RL-based approaches struggle to solve most of the tasks efficiently; 2) gradient-based approaches, by optimizing open-loop control sequences with the built-in differentiable physics engine, can rapidly find a solution within tens of iterations, but still fall short on multi-stage tasks that require long-term planning.

Reinforcement Learning (RL)

Learning Task Decomposition with Ordered Memory Policy Network

no code implementations19 Mar 2021 Yuchen Lu, Yikang Shen, Siyuan Zhou, Aaron Courville, Joshua B. Tenenbaum, Chuang Gan

The discovered subtask hierarchy could be used to perform task decomposition, recovering the subtask boundaries in an unstruc-tured demonstration.

Inductive Bias

From Pixel to Patch: Synthesize Context-aware Features for Zero-shot Semantic Segmentation

1 code implementation25 Sep 2020 Zhangxuan Gu, Siyuan Zhou, Li Niu, Zihan Zhao, Liqing Zhang

Thus, we focus on zero-shot semantic segmentation, which aims to segment unseen objects with only category-level semantic representations provided for unseen categories.

Image Classification Semantic Segmentation +1

Context-aware Feature Generation for Zero-shot Semantic Segmentation

2 code implementations16 Aug 2020 Zhangxuan Gu, Siyuan Zhou, Li Niu, Zihan Zhao, Liqing Zhang

In this paper, we propose a novel context-aware feature generation method for zero-shot segmentation named CaGNet.

Semantic Segmentation Word Embeddings +1

Transferable Interactiveness Knowledge for Human-Object Interaction Detection

3 code implementations CVPR 2019 Yong-Lu Li, Siyuan Zhou, Xijie Huang, Liang Xu, Ze Ma, Hao-Shu Fang, Yan-Feng Wang, Cewu Lu

On account of the generalization of interactiveness, interactiveness network is a transferable knowledge learner and can be cooperated with any HOI detection models to achieve desirable results.

Human-Object Interaction Detection

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