Search Results for author: Yun-hui Liu

Found 27 papers, 9 papers with code

Globally Optimal and Efficient Vanishing Point Estimation in Atlanta World

no code implementations ECCV 2020 Haoang Li, Pyojin Kim, Ji Zhao, Kyungdon Joo, Zhipeng Cai, Zhe Liu , Yun-hui Liu

In Atlanta world, given a set of image lines, we aim to cluster them by the unknown-but-sought VPs whose number is unknown.

Efficient Map Sparsification Based on 2D and 3D Discretized Grids

1 code implementation CVPR 2023 XiaoYu Zhang, Yun-hui Liu

Furthermore, to reduce the influence of different spatial distributions between the mapping and query sequences, which is not considered in previous methods, we also introduce a space constraint term based on 3D discretized grids.

Autonomous Navigation

OmniVidar: Omnidirectional Depth Estimation From Multi-Fisheye Images

1 code implementation CVPR 2023 Sheng Xie, Daochuan Wang, Yun-hui Liu

Estimating depth from four large field of view (FoV) cameras has been a difficult and understudied problem.

Depth Estimation

DDIT: Semantic Scene Completion via Deformable Deep Implicit Templates

no code implementations ICCV 2023 Haoang Li, Jinhu Dong, Binghui Wen, Ming Gao, Tianyu Huang, Yun-hui Liu, Daniel Cremers

It abstracts the shape prior of a category, and thus can provide constraints on the overall shape of an instance.

Learning Accurate 3D Shape Based on Stereo Polarimetric Imaging

no code implementations CVPR 2023 Tianyu Huang, Haoang Li, Kejing He, Congying Sui, Bin Li, Yun-hui Liu

As to the orthographic projection problem, we propose a novel Viewing Direction-aided Positional Encoding (VDPE) strategy.

StereoPose: Category-Level 6D Transparent Object Pose Estimation from Stereo Images via Back-View NOCS

no code implementations3 Nov 2022 Kai Chen, Stephen James, Congying Sui, Yun-hui Liu, Pieter Abbeel, Qi Dou

To further improve the performance of the stereo framework, StereoPose is equipped with a parallax attention module for stereo feature fusion and an epipolar loss for improving the stereo-view consistency of network predictions.

Object Pose Estimation +1

Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Picking

no code implementations14 Apr 2022 Kai Chen, Rui Cao, Stephen James, Yichuan Li, Yun-hui Liu, Pieter Abbeel, Qi Dou

To continuously improve the quality of pseudo labels, we iterate the above steps by taking the trained student model as a new teacher and re-label real data using the refined teacher model.

6D Pose Estimation using RGB Robotic Grasping

Deterministic Point Cloud Registration via Novel Transformation Decomposition

no code implementations CVPR 2022 Wen Chen, Haoang Li, Qiang Nie, Yun-hui Liu

Given a set of putative 3D-3D point correspondences, we aim to remove outliers and estimate rigid transformation with 6 degrees of freedom (DOF).

Point Cloud Registration

SurRoL: An Open-source Reinforcement Learning Centered and dVRK Compatible Platform for Surgical Robot Learning

1 code implementation30 Aug 2021 Jiaqi Xu, Bin Li, Bo Lu, Yun-hui Liu, Qi Dou, Pheng-Ann Heng

Ten learning-based surgical tasks are built in the platform, which are common in the real autonomous surgical execution.

Reinforcement Learning (RL)

One to Many: Adaptive Instrument Segmentation via Meta Learning and Dynamic Online Adaptation in Robotic Surgical Video

no code implementations24 Mar 2021 Zixu Zhao, Yueming Jin, Bo Lu, Chi-Fai Ng, Qi Dou, Yun-hui Liu, Pheng-Ann Heng

To greatly increase the label efficiency, we explore a new problem, i. e., adaptive instrument segmentation, which is to effectively adapt one source model to new robotic surgical videos from multiple target domains, only given the annotated instruments in the first frame.

General Knowledge Meta-Learning

Self-supervised Video Representation Learning by Uncovering Spatio-temporal Statistics

2 code implementations31 Aug 2020 Jiangliu Wang, Jianbo Jiao, Linchao Bao, Shengfeng He, Wei Liu, Yun-hui Liu

Specifically, given an unlabeled video clip, we compute a series of spatio-temporal statistical summaries, such as the spatial location and dominant direction of the largest motion, the spatial location and dominant color of the largest color diversity along the temporal axis, etc.

Action Recognition Representation Learning +3

Self-supervised Video Representation Learning by Pace Prediction

1 code implementation ECCV 2020 Jiangliu Wang, Jianbo Jiao, Yun-hui Liu

This paper addresses the problem of self-supervised video representation learning from a new perspective -- by video pace prediction.

Action Recognition Contrastive Learning +3

Unsupervised 3D Human Pose Representation with Viewpoint and Pose Disentanglement

1 code implementation ECCV 2020 Qiang Nie, Ziwei Liu, Yun-hui Liu

Learning a good 3D human pose representation is important for human pose related tasks, e. g. human 3D pose estimation and action recognition.

3D Pose Estimation Action Recognition +2

HMTNet:3D Hand Pose Estimation from Single Depth Image Based on Hand Morphological Topology

no code implementations12 Nov 2019 Weiguo Zhou, Xin Jiang, Chen Chen, Sijia Mei, Yun-hui Liu

In this paper, we propose a method that takes advantage of human hand morphological topology (HMT) structure to improve the pose estimation performance.

Robotics Human-Computer Interaction

Assembly of randomly placed parts realized by using only one robot arm with a general parallel-jaw gripper

no code implementations19 Sep 2019 Jie Zhao, Xin Jiang, Xiaoman Wang, Shengfan Wang, Yun-hui Liu

The proposal in this paper is verified by a simulated assembly in which a robot arm completed the assembly process including parts picking from bin and a subsequent peg-in-hole assembly.

Efficient Fully Convolution Neural Network for Generating Pixel Wise Robotic Grasps With High Resolution Images

no code implementations24 Feb 2019 Shengfan Wang, Xin Jiang, Jie Zhao, Xiaoman Wang, Weiguo Zhou, Yun-hui Liu, Fellow IEEE

This paper presents an efficient neural network model to generate robotic grasps with high resolution images.


LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis

2 code implementations ICCV 2019 Zhe Liu, Shunbo Zhou, Chuanzhe Suo, Yingtian Liu, Peng Yin, Hesheng Wang, Yun-hui Liu

Point cloud based place recognition is still an open issue due to the difficulty in extracting local features from the raw 3D point cloud and generating the global descriptor, and it's even harder in the large-scale dynamic environments.

Point Cloud Retrieval Retrieval +1

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