Search Results for author: Wei Jing

Found 20 papers, 6 papers with code

LASIL: Learner-Aware Supervised Imitation Learning For Long-term Microscopic Traffic Simulation

no code implementations26 Mar 2024 Ke Guo, Zhenwei Miao, Wei Jing, Weiwei Liu, Weizi Li, Dayang Hao, Jia Pan

Due to the covariate shift issue, existing imitation learning-based simulators often fail to generate stable long-term simulations.

Imitation Learning

ProIn: Learning to Predict Trajectory Based on Progressive Interactions for Autonomous Driving

no code implementations25 Mar 2024 Yinke Dong, Haifeng Yuan, Hongkun Liu, Wei Jing, Fangzhen Li, Hongmin Liu, Bin Fan

In this work, a progressive interaction network is proposed to enable the agent's feature to progressively focus on relevant maps, in order to better learn agents' feature representation capturing the relevant map constraints.

Autonomous Driving motion prediction

FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving

1 code implementation2 Aug 2023 Tengju Ye, Wei Jing, Chunyong Hu, Shikun Huang, Lingping Gao, Fangzhen Li, Jingke Wang, Ke Guo, Wencong Xiao, Weibo Mao, Hang Zheng, Kun Li, Junbo Chen, Kaicheng Yu

Building a multi-modality multi-task neural network toward accurate and robust performance is a de-facto standard in perception task of autonomous driving.

Autonomous Driving

Hierarchical Point Cloud Encoding and Decoding with Lightweight Self-Attention based Model

no code implementations13 Feb 2022 En Yen Puang, Hao Zhang, Hongyuan Zhu, Wei Jing

In this paper we present SA-CNN, a hierarchical and lightweight self-attention based encoding and decoding architecture for representation learning of point cloud data.

Representation Learning Retrieval

End-to-end Reinforcement Learning of Robotic Manipulation with Robust Keypoints Representation

no code implementations12 Feb 2022 Tianying Wang, En Yen Puang, Marcus Lee, Yan Wu, Wei Jing

The proposed method learns keypoints from camera images as the state representation, through a self-supervised autoencoder architecture.

reinforcement-learning Reinforcement Learning (RL)

Temporal Sentence Grounding in Videos: A Survey and Future Directions

no code implementations20 Jan 2022 Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

Temporal sentence grounding in videos (TSGV), \aka natural language video localization (NLVL) or video moment retrieval (VMR), aims to retrieve a temporal moment that semantically corresponds to a language query from an untrimmed video.

Moment Retrieval Retrieval +2

Towards Debiasing Temporal Sentence Grounding in Video

no code implementations8 Nov 2021 Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

In this paper, we propose two debiasing strategies, data debiasing and model debiasing, to "force" a TSGV model to capture cross-modal interactions.

Sentence Temporal Sentence Grounding

Fault-Tolerant Federated Reinforcement Learning with Theoretical Guarantee

2 code implementations NeurIPS 2021 Flint Xiaofeng Fan, Yining Ma, Zhongxiang Dai, Wei Jing, Cheston Tan, Bryan Kian Hsiang Low

The growing literature of Federated Learning (FL) has recently inspired Federated Reinforcement Learning (FRL) to encourage multiple agents to federatively build a better decision-making policy without sharing raw trajectories.

Decision Making Federated Learning +2

Domain Generalization for Vision-based Driving Trajectory Generation

1 code implementation22 Sep 2021 Yunkai Wang, Dongkun Zhang, Yuxiang Cui, Zexi Chen, Wei Jing, Junbo Chen, Rong Xiong, Yue Wang

In this paper, we propose a domain generalization method for vision-based driving trajectory generation for autonomous vehicles in urban environments, which can be seen as a solution to extend the Invariant Risk Minimization (IRM) method in complex problems.

Autonomous Vehicles Domain Generalization

Parallel Attention Network with Sequence Matching for Video Grounding

no code implementations Findings (ACL) 2021 Hao Zhang, Aixin Sun, Wei Jing, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh

In this work, we propose a Parallel Attention Network with Sequence matching (SeqPAN) to address the challenges in this task: multi-modal representation learning, and target moment boundary prediction.

Representation Learning Video Grounding

Video Corpus Moment Retrieval with Contrastive Learning

1 code implementation13 May 2021 Hao Zhang, Aixin Sun, Wei Jing, Guoshun Nan, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh

We adopt the first approach and introduce two contrastive learning objectives to refine video encoder and text encoder to learn video and text representations separately but with better alignment for VCMR.

Contrastive Learning Moment Retrieval +2

Context Modeling with Evidence Filter for Multiple Choice Question Answering

no code implementations6 Oct 2020 Sicheng Yu, Hao Zhang, Wei Jing, Jing Jiang

In addition to the effective reduction of human efforts of our approach compared, through extensive experiments on OpenbookQA, we show that the proposed approach outperforms the models that use the same backbone and more training data; and our parameter analysis also demonstrates the interpretability of our approach.

Machine Reading Comprehension Multiple-choice +1

KOVIS: Keypoint-based Visual Servoing with Zero-Shot Sim-to-Real Transfer for Robotics Manipulation

1 code implementation28 Jul 2020 En Yen Puang, Keng Peng Tee, Wei Jing

We train the deep neural network only in the simulated environment; and the trained model could be directly used for real-world visual servoing tasks.

Data Augmentation Self-Supervised Learning

Span-based Localizing Network for Natural Language Video Localization

1 code implementation ACL 2020 Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

Given an untrimmed video and a text query, natural language video localization (NLVL) is to locate a matching span from the video that semantically corresponds to the query.

Efficient Robotic Task Generalization Using Deep Model Fusion Reinforcement Learning

no code implementations11 Dec 2019 Tianying Wang, Hao Zhang, Wei Qi Toh, Hongyuan Zhu, Cheston Tan, Yan Wu, Yong liu, Wei Jing

The proposed method is able to efficiently generalize the previously learned task by model fusion to solve the environment adaptation problem.

reinforcement-learning Reinforcement Learning (RL)

RoboCoDraw: Robotic Avatar Drawing with GAN-based Style Transfer and Time-efficient Path Optimization

no code implementations11 Dec 2019 Tianying Wang, Wei Qi Toh, Hao Zhang, Xiuchao Sui, Shaohua Li, Yong liu, Wei Jing

The proposed RoboCoDraw system takes a real human face image as input, converts it to a stylized avatar, then draws it with a robotic arm.

Robotics Graphics

6D Pose Estimation with Correlation Fusion

no code implementations24 Sep 2019 Yi Cheng, Hongyuan Zhu, Ying Sun, Cihan Acar, Wei Jing, Yan Wu, Liyuan Li, Cheston Tan, Joo-Hwee Lim

To our best knowledge, this is the first work to explore effective intra- and inter-modality fusion in 6D pose estimation.

6D Pose Estimation 6D Pose Estimation using RGB

Coverage Path Planning using Path Primitive Sampling and Primitive Coverage Graph for Visual Inspection

no code implementations 2019年8月8日 2019 Wei Jing, Di Deng2, Zhe Xiao3, Yong Liu1, Kenji Shimada2

In this paper, we propose a novel planning method to directly sample and plan the inspection path for a camera-equipped UAV to acquire visual and geometric information of the target structures as a video stream setting in complex 3D environment.

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