b'Yuwei Wu'

research

∙ 06/30/2023

Neural 3D Scene Reconstruction from Multiple 2D Images without 3D Supervision

Neural 3D scene reconstruction methods have achieved impressive performa...

0 Yi Guo, et al. ∙

research

∙ 05/19/2023

Fast-StrucTexT: An Efficient Hourglass Transformer with Modality-guided Dynamic Token Merge for Document Understanding

Transformers achieve promising performance in document understanding bec...

0 Mingliang Zhai, et al. ∙

research

∙ 05/11/2023

Learning-Free Grasping of Unknown Objects Using Hidden Superquadrics

Robotic grasping is an essential and fundamental task and has been studi...

0 Yuwei Wu, et al. ∙

research

∙ 03/23/2023

Marching-Primitives: Shape Abstraction from Signed Distance Function

Representing complex objects with basic geometric primitives has long be...

0 Weixiao Liu, et al. ∙

research

∙ 09/23/2022

Multi-Agent Exploration of an Unknown Sparse Landmark Complex via Deep Reinforcement Learning

In recent years Landmark Complexes have been successfully employed for l...

0 Xiatao Sun, et al. ∙

research

∙ 09/22/2022

SEER: Safe Efficient Exploration for Aerial Robots using Learning to Predict Information Gain

We address the problem of efficient 3-D exploration in indoor environmen...

0 Yuezhan Tao, et al. ∙

research

∙ 08/28/2022

Differential Flatness-Based Trajectory Planning for Autonomous Vehicles

As a core part of autonomous driving systems, motion planning has receiv...

0 Zhichao Han, et al. ∙

research

∙ 05/25/2022

Primitive3D: 3D Object Dataset Synthesis from Randomly Assembled Primitives

Numerous advancements in deep learning can be attributed to the access t...

0 Xinke Li, et al. ∙

research

∙ 03/28/2022

Primitive-based Shape Abstraction via Nonparametric Bayesian Inference

3D shape abstraction has drawn great interest over the years. Apart from...

0 Yuwei Wu, et al. ∙

research

∙ 11/29/2021

Robust and Accurate Superquadric Recovery: a Probabilistic Approach

Interpreting objects with basic geometric primitives has long been studi...

0 Weixiao Liu, et al. ∙

research

∙ 05/10/2021

GroupLink: An End-to-end Multitask Method for Word Grouping and Relation Extraction in Form Understanding

Forms are a common type of document in real life and carry rich informat...

0 Zilong Wang, et al. ∙

research

∙ 04/15/2021

A Decomposition Model for Stereo Matching

In this paper, we present a decomposition model for stereo matching to s...

0 Chengtang Yao, et al. ∙

research

∙ 04/14/2021

A Hyperbolic-to-Hyperbolic Graph Convolutional Network

Hyperbolic graph convolutional networks (GCNs) demonstrate powerful repr...

0 Jindou Dai, et al. ∙

research

∙ 03/20/2021

External Forces Resilient Safe Motion Planning for Quadrotor

Adaptive autonomous navigation with no prior knowledge of extraneous dis...

0 Yuwei Wu, et al. ∙

research

∙ 12/27/2020

SG-Net: Syntax Guided Transformer for Language Representation

Understanding human language is one of the key themes of artificial inte...

6 Zhuosheng Zhang, et al. ∙

research

∙ 10/17/2020

Generating Large Convex Polytopes Directly on Point Clouds

In this paper, we present a method to efficiently generate large, free, ...

0 Xingguang Zhong, et al. ∙

research

∙ 08/11/2020

Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene

Learning on 3D scene-based point cloud has received extensive attention ...

0 Xinke Li, et al. ∙

research

∙ 06/05/2020

Content-Aware Inter-Scale Cost Aggregation for Stereo Matching

Cost aggregation is a key component of stereo matching for high-quality ...

0 Chengtang Yao, et al. ∙

research

∙ 04/23/2020

Semi-Supervised Models via Data Augmentationfor Classifying Interactive Affective Responses

We present semi-supervised models with data augmentation (SMDA), a semi-...

0 Jiaao Chen, et al. ∙

research

∙ 09/05/2019

Semantics-aware BERT for Language Understanding

The latest work on language representations carefully integrates context...

0 Zhuosheng Zhang, et al. ∙

research

∙ 08/30/2019

DCMN+: Dual Co-Matching Network for Multi-choice Reading Comprehension

Multi-choice reading comprehension is a challenging task to select an an...

0 Shuailiang Zhang, et al. ∙

research

∙ 08/14/2019

SG-Net: Syntax-Guided Machine Reading Comprehension

For machine reading comprehension, how to effectively model the linguist...

0 Zhuosheng Zhang, et al. ∙

research

∙ 03/15/2019

Stitching Videos from a Fisheye Lens Camera and a Wide-Angle Lens Camera for Telepresence Robots

Many telepresence robots are equipped with a forward-facing camera for v...

0 Yanmei Dong, et al. ∙

research

∙ 01/27/2019

Dual Co-Matching Network for Multi-choice Reading Comprehension

Multi-choice reading comprehension is a challenging task that requires c...

0 Shuailiang Zhang, et al. ∙

research

∙ 01/13/2019

Auto-Retoucher(ART) - A framework for Background Replacement and Image Editing

Replacing the background and simultaneously adjusting foreground objects...

0 Yunxuan Xiao, et al. ∙

research

∙ 09/08/2018

I Know What You Want: Semantic Learning for Text Comprehension

Who did what to whom is a major focus in natural language understanding,...

0 Zhuosheng Zhang, et al. ∙

research

∙ 01/12/2018

Deep Stereo Matching with Explicit Cost Aggregation Sub-Architecture

Deep neural networks have shown excellent performance for stereo matchin...

0 Lidong Yu, et al. ∙

research

∙ 11/17/2017

Learning a Robust Representation via a Deep Network on Symmetric Positive Definite Manifolds

Recent studies have shown that aggregating convolutional features of a p...

0 Zhi Gao, et al. ∙

research

∙ 03/31/2017

A Hybrid Data Association Framework for Robust Online Multi-Object Tracking

Global optimization algorithms have shown impressive performance in data...

0 Min Yang, et al. ∙

Yuwei Wu

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