Search Results for author: Yimin Chen

Found 13 papers, 9 papers with code

Pseudo-mask Matters in Weakly-supervised Semantic Segmentation

1 code implementation30 Aug 2021 Yi Li, Zhanghui Kuang, Liyang Liu, Yimin Chen, Wayne Zhang

For these matters, we propose the following designs to push the performance to new state-of-art: (i) Coefficient of Variation Smoothing to smooth the CAMs adaptively; (ii) Proportional Pseudo-mask Generation to project the expanded CAMs to pseudo-mask based on a new metric indicating the importance of each class on each location, instead of the scores trained from binary classifiers.

Weakly-Supervised Semantic Segmentation

Slender Object Detection: Diagnoses and Improvements

1 code implementation17 Nov 2020 Zhaoyi Wan, Yimin Chen, Sutao Deng, Kunpeng Chen, Cong Yao, Jiebo Luo

In this paper, we are concerned with the detection of a particular type of objects with extreme aspect ratios, namely \textbf{slender objects}.

Object Detection

Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching

2 code implementations9 Sep 2019 Youmin Zhang, Yimin Chen, Xiao Bai, Suihanjin Yu, Kun Yu, Zhiwei Li, Kuiyuan Yang

However, disparity is just a byproduct of a matching process modeled by cost volume, while indirectly learning cost volume driven by disparity regression is prone to overfitting since the cost volume is under constrained.

Disparity Estimation Stereo Matching +1

Fashion Retrieval via Graph Reasoning Networks on a Similarity Pyramid

no code implementations ICCV 2019 Zhanghui Kuang, Yiming Gao, Guanbin Li, Ping Luo, Yimin Chen, Liang Lin, Wayne Zhang

To address this issue, we propose a novel Graph Reasoning Network (GRNet) on a Similarity Pyramid, which learns similarities between a query and a gallery cloth by using both global and local representations in multiple scales.

Image Retrieval

Data-Driven Neuron Allocation for Scale Aggregation Networks

1 code implementation CVPR 2019 Yi Li, Zhanghui Kuang, Yimin Chen, Wayne Zhang

The most informative output neurons in each block are preserved while others are discarded, and thus neurons for multiple scales are competitively and adaptively allocated.

Image Classification Object Detection

Learning Efficient Detector with Semi-supervised Adaptive Distillation

1 code implementation2 Jan 2019 Shitao Tang, Litong Feng, Wenqi Shao, Zhanghui Kuang, Wei zhang, Yimin Chen

ADL enlarges the distillation loss for hard-to-learn and hard-to-mimic samples and reduces distillation loss for the dominant easy samples, enabling distillation to work on the single-stage detector first time, even if the student and the teacher are identical.

Image Classification Knowledge Distillation +1

Learning Segmentation Masks with the Independence Prior

no code implementations12 Nov 2018 Songmin Dai, Xiaoqiang Li, Lu Wang, Pin Wu, Weiqin Tong, Yimin Chen

We get appealing results in both tasks, which shows the independence prior is useful for instance segmentation and it is possible to unsupervisedly learn instance masks with only one image.

Instance Segmentation Weakly-Supervised Semantic Segmentation

Fast Video Shot Transition Localization with Deep Structured Models

3 code implementations13 Aug 2018 Shitao Tang, Litong Feng, Zhangkui Kuang, Yimin Chen, Wei zhang

In order to train a high-performance shot transition detector, we contribute a new database ClipShots, which contains 128636 cut transitions and 38120 gradual transitions from 4039 online videos.

Instance-level Human Parsing via Part Grouping Network

1 code implementation ECCV 2018 Ke Gong, Xiaodan Liang, Yicheng Li, Yimin Chen, Ming Yang, Liang Lin

Instance-level human parsing towards real-world human analysis scenarios is still under-explored due to the absence of sufficient data resources and technical difficulty in parsing multiple instances in a single pass.

Edge Detection Human Parsing +2

Toward Characteristic-Preserving Image-based Virtual Try-On Network

3 code implementations ECCV 2018 Bochao Wang, Huabin Zheng, Xiaodan Liang, Yimin Chen, Liang Lin, Meng Yang

Second, to alleviate boundary artifacts of warped clothes and make the results more realistic, we employ a Try-On Module that learns a composition mask to integrate the warped clothes and the rendered image to ensure smoothness.

Geometric Matching Virtual Try-on

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