Search Results for author: Di Chen

Found 34 papers, 7 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.

Divide and Conquer: Hybrid Pre-training for Person Search

1 code implementation13 Dec 2023 Yanling Tian, Di Chen, Yunan Liu, Jian Yang, Shanshan Zhang

To the best of our knowledge, this is the first work that investigates how to support full-task pre-training using sub-task data.

Human Detection Person Search

Ranni: Taming Text-to-Image Diffusion for Accurate Instruction Following

no code implementations28 Nov 2023 Yutong Feng, Biao Gong, Di Chen, Yujun Shen, Yu Liu, Jingren Zhou

Existing text-to-image (T2I) diffusion models usually struggle in interpreting complex prompts, especially those with quantity, object-attribute binding, and multi-subject descriptions.

Attribute Denoising +1

Data-driven Traffic Simulation: A Comprehensive Review

no code implementations24 Oct 2023 Di Chen, Meixin Zhu, Hao Yang, Xuesong Wang, Yinhai Wang

The primary objective of this paper is to review current research efforts and provide a futuristic perspective that will benefit future developments in the field.

Autonomous Driving Imitation Learning

Composer: Creative and Controllable Image Synthesis with Composable Conditions

5 code implementations20 Feb 2023 Lianghua Huang, Di Chen, Yu Liu, Yujun Shen, Deli Zhao, Jingren Zhou

Recent large-scale generative models learned on big data are capable of synthesizing incredible images yet suffer from limited controllability.

Image Colorization Image-to-Image Translation +3

Grouped Adaptive Loss Weighting for Person Search

no code implementations23 Sep 2022 Yanling Tian, Di Chen, Yunan Liu, Shanshan Zhang, Jian Yang

A straightforward solution is to manually assign different weights to different tasks, compensating for the diverse convergence rates.

Model Optimization Multi-Task Learning +2

Monitoring Vegetation From Space at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-Net

no code implementations16 Jul 2022 Joshua Fan, Di Chen, Jiaming Wen, Ying Sun, Carla P. Gomes

This poses a challenging coarsely-supervised regression (or downscaling) task; at training time, we only have SIF labels at a coarse resolution (3km), but we want to predict SIF at much finer spatial resolutions (e. g. 30m, a 100x increase).

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

1 code implementation 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 +5

Keypoint Message Passing for Video-based Person Re-Identification

1 code implementation16 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

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.

BIG-bench Machine Learning 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 +2

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 In Videos Image Captioning +3

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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