Search Results for author: Yu-cheng Chen

Found 10 papers, 1 papers with code

Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Balance Analysis

1 code implementation30 Aug 2024 Chiu-Chou Lin, Yu-Wei Shih, Kuei-Ting Kuo, Yu-cheng Chen, Chien-Hua Chen, Wei-Chen Chiu, I-Chen Wu

The accuracy of the observed strength relations in these games is comparable to traditional pairwise win value predictions, while also offering a more manageable complexity for analysis.

Card Games Game Design +3

Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice

no code implementations16 Feb 2024 Tanner Fiez, Houssam Nassif, Yu-cheng Chen, Sergio Gamez, Lalit Jain

Adaptive experimental design (AED) methods are increasingly being used in industry as a tool to boost testing throughput or reduce experimentation cost relative to traditional A/B/N testing methods.

counterfactual Counterfactual Inference +2

Monocular Human Pose Estimation: A Survey of Deep Learning-based Methods

no code implementations2 Jun 2020 Yu-cheng Chen, YingLi Tian, Mingyi He

Vision-based monocular human pose estimation, as one of the most fundamental and challenging problems in computer vision, aims to obtain posture of the human body from input images or video sequences.

3D Human Pose Estimation Deep Learning

Self-supervised Modal and View Invariant Feature Learning

no code implementations28 May 2020 Longlong Jing, Yu-cheng Chen, Ling Zhang, Mingyi He, YingLi Tian

By exploring the inherent multi-modality attributes of 3D objects, in this paper, we propose to jointly learn modal-invariant and view-invariant features from different modalities including image, point cloud, and mesh with heterogeneous networks for 3D data.

Cross-Modal Retrieval Retrieval

Self-supervised Feature Learning by Cross-modality and Cross-view Correspondences

no code implementations13 Apr 2020 Longlong Jing, Yu-cheng Chen, Ling Zhang, Mingyi He, YingLi Tian

Specifically, 2D image features of rendered images from different views are extracted by a 2D convolutional neural network, and 3D point cloud features are extracted by a graph convolution neural network.

3D Part Segmentation 3D Shape Classification +4

A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization

no code implementations8 Jun 2019 Yu-cheng Chen, Matus Telgarsky, Chao Zhang, Bolton Bailey, Daniel Hsu, Jian Peng

This paper provides a simple procedure to fit generative networks to target distributions, with the goal of a small Wasserstein distance (or other optimal transport costs).

Coarse-to-fine Semantic Segmentation from Image-level Labels

no code implementations28 Dec 2018 Longlong Jing, Yu-cheng Chen, YingLi Tian

The enhanced coarse mask is fed to a fully convolutional neural network to be recursively refined.

Foreground Segmentation Object +2

Skeleton Boxes: Solving skeleton based action detection with a single deep convolutional neural network

no code implementations19 Apr 2017 Bo Li, Huahui Chen, Yu-cheng Chen, Yuchao Dai, Mingyi He

However, due to the difficulty in representing the 3D skeleton video and the lack of training data, action detection from streaming 3D skeleton video still lags far behind its recognition counterpart and image based object detection.

Action Detection Action Recognition +3

Skeleton based action recognition using translation-scale invariant image mapping and multi-scale deep cnn

no code implementations19 Apr 2017 Bo Li, Mingyi He, Xuelian Cheng, Yu-cheng Chen, Yuchao Dai

Especially on the largest and challenge NTU RGB+D, UTD-MHAD, and MSRC-12 dataset, our method outperforms other methods by a large margion, which proves the efficacy of the proposed method.

Action Recognition Image Classification +3

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