Search Results for author: Wenqiang Xu

Found 15 papers, 7 papers with code

AKB-48: A Real-World Articulated Object Knowledge Base

no code implementations17 Feb 2022 Liu Liu, Wenqiang Xu, Haoyuan Fu, Sucheng Qian, Yang Han, Cewu Lu

To bridge the gap, we present AKB-48: a large-scale Articulated object Knowledge Base which consists of 2, 037 real-world 3D articulated object models of 48 categories.

Object Reconstruction Pose Estimation

iSeg3D: An Interactive 3D Shape Segmentation Tool

no code implementations24 Dec 2021 Sucheng Qian, Liu Liu, Wenqiang Xu, Cewu Lu

It can obtain a satisfied segmentation result with minimal human clicks (< 10).

OMAD: Object Model with Articulated Deformations for Pose Estimation and Retrieval

no code implementations14 Dec 2021 Han Xue, Liu Liu, Wenqiang Xu, Haoyuan Fu, Cewu Lu

With the full representation of the object shape and joint states, we can address several tasks including category-level object pose estimation and the articulated object retrieval.

Pose Estimation

SAGCI-System: Towards Sample-Efficient, Generalizable, Compositional, and Incremental Robot Learning

no code implementations29 Nov 2021 Jun Lv, Qiaojun Yu, Lin Shao, Wenhai Liu, Wenqiang Xu, Cewu Lu

We apply our system to perform articulated object manipulation tasks, both in the simulation and the real world.

ContourRender: Detecting Arbitrary Contour Shape For Instance Segmentation In One Pass

no code implementations7 Jun 2021 Tutian Tang, Wenqiang Xu, Ruolin Ye, Yan-Feng Wang, Cewu Lu

In addition, we specifically select a subset from COCO val2017 named COCO ContourHard-val to further demonstrate the contour quality improvements.

Instance Segmentation Semantic Segmentation

Towards Real-World Category-level Articulation Pose Estimation

no code implementations7 May 2021 Liu Liu, Han Xue, Wenqiang Xu, Haoyuan Fu, Cewu Lu

This setting allows varied kinematic structures within a semantic category, and multiple instances to co-exist in an observation of real world.

Mixed Reality Pose Estimation

H2O: A Benchmark for Visual Human-human Object Handover Analysis

no code implementations ICCV 2021 Ruolin Ye, Wenqiang Xu, Zhendong Xue, Tutian Tang, Yanfeng Wang, Cewu Lu

Besides, we also report the hand and object pose errors with existing baselines and show that the dataset can serve as the video demonstrations for robot imitation learning on the handover task.

Imitation Learning

CPF: Learning a Contact Potential Field to Model the Hand-Object Interaction

1 code implementation ICCV 2021 Lixin Yang, Xinyu Zhan, Kailin Li, Wenqiang Xu, Jiefeng Li, Cewu Lu

In this paper, we present an explicit contact representation namely Contact Potential Field (CPF), and a learning-fitting hybrid framework namely MIHO to Modeling the Interaction of Hand and Object.

Pose Estimation

Learning Universal Shape Dictionary for Realtime Instance Segmentation

1 code implementation2 Dec 2020 Tutian Tang, Wenqiang Xu, Ruolin Ye, Lixin Yang, Cewu Lu

First, it learns a dictionary from a large collection of shape datasets, making any shape being able to be decomposed into a linear combination through the dictionary.

Explainable Models Instance Segmentation +1

BiHand: Recovering Hand Mesh with Multi-stage Bisected Hourglass Networks

1 code implementation12 Aug 2020 Lixin Yang, Jiasen Li, Wenqiang Xu, Yiqun Diao, Cewu Lu

Inside each stage, BiHand adopts a novel bisecting design which allows the networks to encapsulate two closely related information (e. g. 2D keypoints and silhouette in 2D seeding stage, 3D joints, and depth map in 3D lifting stage, joint rotations and shape parameters in the mesh generation stage) in a single forward pass.

Pose Tracking

RGB-D Individual Segmentation

no code implementations16 Oct 2019 Wenqiang Xu, Yanjun Fu, Yuchen Luo, Chang Liu, Cewu Lu

Fine-grained recognition task deals with sub-category classification problem, which is important for real-world applications.

Explicit Shape Encoding for Real-Time Instance Segmentation

1 code implementation ICCV 2019 Wenqiang Xu, Haiyang Wang, Fubo Qi, Cewu Lu

In this paper, we propose a novel top-down instance segmentation framework based on explicit shape encoding, named \textbf{ESE-Seg}.

Object Detection Real-time Instance Segmentation +1

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