Search Results for author: Di Chen

Found 27 papers, 3 papers with code

Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning

no code implementations ICML 2020 Di Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John Gregoire, Carla Gomes

We introduce Deep Reasoning Networks (DRNets), an end-to-end framework that combines deep learning with constraint reasoning for solving pattern de-mixing problems, typically in an unsupervised or very-weakly-supervised setting.

PoseTrack21: A Dataset for Person Search, Multi-Object Tracking and Multi-Person Pose Tracking

no code implementations CVPR 2022 Andreas Döring, Di Chen, Shanshan Zhang, Bernt Schiele, Jürgen Gall

Current research evaluates person search, multi-object tracking and multi-person pose estimation as separate tasks and on different datasets although these tasks are very akin to each other and comprise similar sub-tasks, e. g. person detection or appearance-based association of detected persons.

Human Detection Multi-Object Tracking +4

Keypoint Message Passing for Video-based Person Re-Identification

no code implementations16 Nov 2021 Di Chen, Andreas Doering, Shanshan Zhang, Jian Yang, Juergen Gall, Bernt Schiele

Video-based person re-identification (re-ID) is an important technique in visual surveillance systems which aims to match video snippets of people captured by different cameras.

Representation Learning Video-Based Person Re-Identification

Automating Crystal-Structure Phase Mapping: Combining Deep Learning with Constraint Reasoning

no code implementations21 Aug 2021 Di Chen, Yiwei Bai, Sebastian Ament, Wenting Zhao, Dan Guevarra, Lan Zhou, Bart Selman, R. Bruce van Dover, John M. Gregoire, Carla P. Gomes

DRNets compensate for the limited data by exploiting and magnifying the rich prior knowledge about the thermodynamic rules governing the mixtures of crystals with constraint reasoning seamlessly integrated into neural network optimization.

Model comparison of DBD-PA-induced body force in quiescent air and separated flow over NACA0015

no code implementations10 Dec 2020 Di Chen, Kengo Asada, Satoshi Sekimoto, Kozo Fujii, Hiroyuki Nishida

The D-D models generate momentarily higher body force in the positive-going phase of the AC power, but activate a smaller flow region than the S-H model with Dc = 0. 0117, which is given by the experiment beforehand at 7kV.

Fluid Dynamics Plasma Physics

PoseTrackReID: Dataset Description

no code implementations12 Nov 2020 Andreas Doering, Di Chen, Shanshan Zhang, Bernt Schiele, Juergen Gall

For that reason, we present PoseTrackReID, a large-scale dataset for multi-person pose tracking and video-based person re-ID.

Pose Tracking Video-Based Person Re-Identification

Block-term Tensor Neural Networks

no code implementations10 Oct 2020 Jinmian Ye, Guangxi Li, Di Chen, Haiqin Yang, Shandian Zhe, Zenglin Xu

Deep neural networks (DNNs) have achieved outstanding performance in a wide range of applications, e. g., image classification, natural language processing, etc.

Image Classification Natural Language Processing

Norm-Aware Embedding for Efficient Person Search

1 code implementation CVPR 2020 Di Chen, Shanshan Zhang, Jian Yang, Bernt Schiele

Person Search is a practically relevant task that aims to jointly solve Person Detection and Person Re-identification (re-ID).

Human Detection Person Re-Identification +1

Task-Based Learning via Task-Oriented Prediction Network with Applications in Finance

no code implementations17 Oct 2019 Di Chen, Yada Zhu, Xiaodong Cui, Carla P. Gomes

Real-world applications often involve domain-specific and task-based performance objectives that are not captured by the standard machine learning losses, but are critical for decision making.

Decision Making

Deep Reasoning Networks: Thinking Fast and Slow, for Pattern De-mixing

no code implementations25 Sep 2019 Di Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John M. Gregoire, Carla P. Gomes

We introduce Deep Reasoning Networks (DRNets), an end-to-end framework that combines deep learning with reasoning for solving pattern de-mixing problems, typically in an unsupervised or weakly-supervised setting.

Deep Reasoning Networks: Thinking Fast and Slow

no code implementations3 Jun 2019 Di Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John M. Gregoire, Carla P. Gomes

At a high level, DRNets encode a structured latent space of the input data, which is constrained to adhere to prior knowledge by a reasoning module.

Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant

no code implementations25 Feb 2019 Johan Bjorck, Brendan H. Rappazzo, Di Chen, Richard Bernstein, Peter H. Wrege, Carla P. Gomes

In this work, we consider applying machine learning to the analysis and compression of audio signals in the context of monitoring elephants in sub-Saharan Africa.

How to "DODGE" Complex Software Analytics?

no code implementations5 Feb 2019 Amritanshu Agrawal, Wei Fu, Di Chen, Xipeng Shen, Tim Menzies

Machine learning techniques applied to software engineering tasks can be improved by hyperparameter optimization, i. e., automatic tools that find good settings for a learner's control parameters.

Hyperparameter Optimization

Bias Reduction via End-to-End Shift Learning: Application to Citizen Science

no code implementations1 Nov 2018 Di Chen, Carla P. Gomes

Citizen science projects are successful at gathering rich datasets for various applications.

Hybrid Neural Attention for Agreement/Disagreement Inference in Online Debates

no code implementations EMNLP 2018 Di Chen, Jiachen Du, Lidong Bing, Ruifeng Xu

Inferring the agreement/disagreement relation in debates, especially in online debates, is one of the fundamental tasks in argumentation mining.

Natural Language Inference Sentiment Analysis

Person Search via A Mask-Guided Two-Stream CNN Model

no code implementations ECCV 2018 Di Chen, Shanshan Zhang, Wanli Ouyang, Jian Yang, Ying Tai

In this work, we tackle the problem of person search, which is a challenging task consisted of pedestrian detection and person re-identification~(re-ID).

Pedestrian Detection Person Re-Identification +1

End-to-End Learning for the Deep Multivariate Probit Model

no code implementations ICML 2018 Di Chen, Yexiang Xue, Carla P. Gomes

The multivariate probit model (MVP) is a popular classic model for studying binary responses of multiple entities.

Texture Segmentation Based Video Compression Using Convolutional Neural Networks

no code implementations8 Feb 2018 Chichen Fu, Di Chen, Edward J. Delp, Zoe Liu, Fengqing Zhu

There has been a growing interest in using different approaches to improve the coding efficiency of modern video codec in recent years as demand for web-based video consumption increases.

Texture Classification Video Compression

BT-Nets: Simplifying Deep Neural Networks via Block Term Decomposition

no code implementations15 Dec 2017 Guangxi Li, Jinmian Ye, Haiqin Yang, Di Chen, Shuicheng Yan, Zenglin Xu

Recently, deep neural networks (DNNs) have been regarded as the state-of-the-art classification methods in a wide range of applications, especially in image classification.

General Classification Image Classification

Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition

no code implementations CVPR 2018 Jinmian Ye, Linnan Wang, Guangxi Li, Di Chen, Shandian Zhe, Xinqi Chu, Zenglin Xu

On three challenging tasks, including Action Recognition in Videos, Image Captioning and Image Generation, BT-RNN outperforms TT-RNN and the standard RNN in terms of both prediction accuracy and convergence rate.

Action Recognition Action Recognition In Videos +4

Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder

no code implementations17 Sep 2017 Luming Tang, Yexiang Xue, Di Chen, Carla P. Gomes

Multi-Entity Dependence Learning (MEDL) explores conditional correlations among multiple entities.

Deep Multi-Species Embedding

no code implementations28 Sep 2016 Di Chen, Yexiang Xue, Shuo Chen, Daniel Fink, Carla Gomes

Additionally, we demonstrate the benefit of using a deep neural network to extract features within the embedding and show how they improve the predictive performance of species distribution modelling.

Relative Error Embeddings for the Gaussian Kernel Distance

no code implementations17 Feb 2016 Di Chen, Jeff M. Phillips

A reproducing kernel can define an embedding of a data point into an infinite dimensional reproducing kernel Hilbert space (RKHS).

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