Jiawei He | DeepAI

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∙ 04/18/2023

You Only Need Two Detectors to Achieve Multi-Modal 3D Multi-Object Tracking

Firstly, a new multi-object tracking framework is proposed in this paper...

0 Xiyang Wang, et al. ∙

∙ 03/27/2023

3D Video Object Detection with Learnable Object-Centric Global Optimization

We explore long-term temporal visual correspondence-based optimization f...

0 Jiawei He, et al. ∙

∙ 03/27/2023

Learnable Graph Matching: A Practical Paradigm for Data Association

Data association is at the core of many computer vision tasks, e.g., mul...

0 Jiawei He, et al. ∙

∙ 03/03/2023

3D Multi-Object Tracking Based on Uncertainty-Guided Data Association

In the existing literature, most 3D multi-object tracking algorithms bas...

0 Jiawei He, et al. ∙

∙ 07/20/2022

Densely Constrained Depth Estimator for Monocular 3D Object Detection

Estimating accurate 3D locations of objects from monocular images is a c...

0 Yingyan Li, et al. ∙

∙ 02/24/2022

DeepFusionMOT: A 3D Multi-Object Tracking Framework Based on Camera-LiDAR Fusion with Deep Association

In the recent literature, on the one hand, many 3D multi-object tracking...

0 Xiyang Wang, et al. ∙

∙ 04/24/2021

Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation

Humans accumulate knowledge in a lifelong fashion. Modern deep neural ne...

0 Mengyao Zhai, et al. ∙

∙ 03/30/2021

Learnable Graph Matching: Incorporating Graph Partitioning with Deep Feature Learning for Multiple Object Tracking

Data association across frames is at the core of Multiple Object Trackin...

0 Jiawei He, et al. ∙

∙ 02/25/2021

Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data

Learning from heterogeneous data poses challenges such as combining data...

0 Yu Gong, et al. ∙

∙ 02/12/2021

Jacobian Determinant of Normalizing Flows

Normalizing flows learn a diffeomorphic mapping between the target and b...

24 Huadong Liao, et al. ∙

∙ 10/07/2020

Improving Sequential Latent Variable Models with Autoregressive Flows

We propose an approach for improving sequence modeling based on autoregr...

0 Joseph Marino, et al. ∙

∙ 03/27/2020

AirRL: A Reinforcement Learning Approach to Urban Air Quality Inference

Urban air pollution has become a major environmental problem that threat...

0 Huiqiang Zhong, et al. ∙

∙ 10/18/2019

Point Process Flows

Event sequences can be modeled by temporal point processes (TPPs) to cap...

0 Nazanin Mehrasa, et al. ∙

∙ 07/24/2019

LayoutVAE: Stochastic Scene Layout Generation from a Label Set

Recently there is an increasing interest in scene generation within the ...

3 Akash Abdu Jyothi, et al. ∙

∙ 07/23/2019

Lifelong GAN: Continual Learning for Conditional Image Generation

Lifelong learning is challenging for deep neural networks due to their s...

7 Mengyao Zhai, et al. ∙

∙ 05/08/2019

Generative Model with Dynamic Linear Flow

Flow-based generative models are a family of exact log-likelihood models...

14 Huadong Liao, et al. ∙

∙ 04/05/2019

A Variational Auto-Encoder Model for Stochastic Point Processes

We propose a novel probabilistic generative model for action sequences. ...

0 Nazanin Mehrasa, et al. ∙

∙ 10/10/2018

SECaps: A Sequence Enhanced Capsule Model for Charge Prediction

Automatic charge prediction aims to predict appropriate final charges ac...

0 Congqing He, et al. ∙

∙ 03/21/2018

Probabilistic Video Generation using Holistic Attribute Control

Videos express highly structured spatio-temporal patterns of visual data...

2 Jiawei He, et al. ∙

∙ 05/30/2017

Generic Tubelet Proposals for Action Localization

We develop a novel framework for action localization in videos. We propo...

0 Jiawei He, et al. ∙