Search Results for author: He Wang

Found 92 papers, 42 papers with code

A Linguistically Motivated Test Suite to Semi-Automatically Evaluate German–English Machine Translation Output

1 code implementation LREC 2022 Vivien Macketanz, Eleftherios Avramidis, Aljoscha Burchardt, He Wang, Renlong Ai, Shushen Manakhimova, Ursula Strohriegel, Sebastian Möller, Hans Uszkoreit

Furthermore, we present various exemplary applications of our test suite that have been implemented in the past years, like contributions to the Conference of Machine Translation, the usage of the test suite and MT outputs for quality estimation, and the expansion of the test suite to the language pair Portuguese–English.

Machine Translation

CHAIRS: Towards Full-Body Articulated Human-Object Interaction

1 code implementation20 Dec 2022 Nan Jiang, Tengyu Liu, Zhexuan Cao, Jieming Cui, Yixin Chen, He Wang, Yixin Zhu, Siyuan Huang

By learning the geometrical relationships in HOI, we devise the very first model that leverage human pose estimation to tackle the estimation of articulated object poses and shapes during whole-body interactions.

Action Recognition Human-Object Interaction Detection +2

3D-Aware Object Goal Navigation via Simultaneous Exploration and Identification

no code implementations1 Dec 2022 Jiazhao Zhang, Liu Dai, Fanpeng Meng, Qingnan Fan, Xuelin Chen, Kai Xu, He Wang

However, leveraging 3D scene representation can be prohibitively unpractical for policy learning in this floor-level task, due to low sample efficiency and expensive computational cost.

Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack

3 code implementations21 Nov 2022 Yunfeng Diao, He Wang, Tianjia Shao, Yong-Liang Yang, Kun Zhou, David Hogg

Via BASAR, we find on-manifold adversarial samples are extremely deceitful and rather common in skeletal motions, in contrast to the common belief that adversarial samples only exist off-manifold.

Adversarial Attack Human Activity Recognition +2

GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts

no code implementations10 Nov 2022 Haoran Geng, Helin Xu, Chengyang Zhao, Chao Xu, Li Yi, Siyuan Huang, He Wang

By identifying and defining 9 GAPart classes (e. g. buttons, handles, etc), we show that our part-centric approach allows our method to learn object perception and manipulation skills from seen object categories and directly generalize to unseen categories.

3D Instance Segmentation Domain Generalization +1

LeNo: Adversarial Robust Salient Object Detection Networks with Learnable Noise

1 code implementation27 Oct 2022 He Wang, Lin Wan, He Tang

In general, LeNo consists of a simple shallow noise and noise estimation that embedded in the encoder and decoder of arbitrary SOD networks respectively.

Noise Estimation object-detection +3

GraspNeRF: Multiview-based 6-DoF Grasp Detection for Transparent and Specular Objects Using Generalizable NeRF

no code implementations12 Oct 2022 Qiyu Dai, Yan Zhu, Yiran Geng, Ciyu Ruan, Jiazhao Zhang, He Wang

In this work, we tackle 6-DoF grasp detection for transparent and specular objects, which is an important yet challenging problem in vision-based robotic systems, due to the failure of depth cameras in sensing their geometry.

Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing

no code implementations8 Oct 2022 Xiaomeng Xu, Yun Liu, Weihang Chen, Haocheng Yuan, He Wang, Jing Xu, Rui Chen, Li Yi

To test our method in real scenarios and enable future studies on generalizable visual-tactile tracking, we collect a real visual-tactile in-hand object pose tracking dataset.

hand-object pose Pose Tracking

DexGraspNet: A Large-Scale Robotic Dexterous Grasp Dataset for General Objects Based on Simulation

no code implementations6 Oct 2022 Ruicheng Wang, Jialiang Zhang, Jiayi Chen, Yinzhen Xu, Puhao Li, Tengyu Liu, He Wang

Compared with the field of object grasping with parallel grippers, dexterous grasping is very under-explored, partially owing to the lack of a large-scale dataset.

Tracking and Reconstructing Hand Object Interactions from Point Cloud Sequences in the Wild

no code implementations24 Sep 2022 Jiayi Chen, Mi Yan, Jiazhao Zhang, Yinzhen Xu, Xiaolong Li, Yijia Weng, Li Yi, Shuran Song, He Wang

We for the first time propose a point cloud based hand joint tracking network, HandTrackNet, to estimate the inter-frame hand joint motion.

hand-object pose Object Tracking +1

Shape Completion with Points in the Shadow

1 code implementation17 Sep 2022 BoWen Zhang, Xi Zhao, He Wang, Ruizhen Hu

The core challenge is to generate plausible geometries to fill the unobserved part of the object based on a partial scan, which is under-constrained and suffers from a huge solution space.

Point Cloud Completion

Talking Head from Speech Audio using a Pre-trained Image Generator

no code implementations9 Sep 2022 Mohammed M. Alghamdi, He Wang, Andrew J. Bulpitt, David C. Hogg

We train a recurrent neural network to map from speech utterances to displacements in the latent space of the image generator.


Domain Randomization-Enhanced Depth Simulation and Restoration for Perceiving and Grasping Specular and Transparent Objects

1 code implementation7 Aug 2022 Qiyu Dai, Jiyao Zhang, Qiwei Li, Tianhao Wu, Hao Dong, Ziyuan Liu, Ping Tan, He Wang

Commercial depth sensors usually generate noisy and missing depths, especially on specular and transparent objects, which poses critical issues to downstream depth or point cloud-based tasks.

Pose Estimation Transparent objects

Human Trajectory Prediction via Neural Social Physics

1 code implementation21 Jul 2022 Jiangbei Yue, Dinesh Manocha, He Wang

Our new model (Neural Social Physics or NSP) is a deep neural network within which we use an explicit physics model with learnable parameters.

Inductive Bias Trajectory Prediction

Space-based gravitational wave signal detection and extraction with deep neural network

no code implementations15 Jul 2022 Tianyu Zhao, Ruoxi Lyu, Zhixiang Ren, He Wang, Zhoujian Cao

Space-based gravitational wave (GW) detectors will be able to observe signals from sources that are otherwise nearly impossible from current ground-based detection.

Underdetermined 2D-DOD and 2D-DOA Estimation for Bistatic Coprime EMVS-MIMO Radar: From the Difference Coarray Perspective

no code implementations6 Jun 2022 Qianpeng Xie, Yihang Du, He Wang, Xiaoyi Pan, Feng Zhao

Firstly, a 5-D tensor model was constructed by using the multi-dimensional space-time characteristics of the received data.

8D Parameters Estimation for Bistatic EMVS-MIMO Radar via the nested PARAFAC

no code implementations4 Jun 2022 Qianpeng Xie, He Wang, Yihang Du, Xiaoyi Pan, Feng Zhao

Firstly, the outer part PARAFAC algorithm was carried out to estimate the receive spatial response matrix and its first way factor matrix.

Real-time Controllable Motion Transition for Characters

no code implementations5 May 2022 Xiangjun Tang, He Wang, Bo Hu, Xu Gong, Ruifan Yi, Qilong Kou, Xiaogang Jin

Then, during generation, we design a transition model which is essentially a sampling strategy to sample from the learned manifold, based on the target frame and the aimed transition duration.

A Practical Two-stage Ranking Framework for Cross-market Recommendation

1 code implementation27 Apr 2022 Zeyuan Chen, He Wang, Xiangyu Zhu, Haiyan Wu, Congcong Gu, Shumeng Liu, Jinchao Huang, Wei zhang

The proposed solution of our team WSDM_Coggle_ is selected as the second place submission.

Attention U-Net as a surrogate model for groundwater prediction

no code implementations9 Apr 2022 Maria Luisa Taccari, Jonathan Nuttall, Xiaohui Chen, He Wang, Bennie Minnema, Peter K. Jimack

This manuscript presents an Attention U-Net model that attempts to capture the fundamental input-output relations of the groundwater system and generates solutions of hydraulic head in the whole domain given a set of physical parameters and boundary conditions.

Multi-Robot Active Mapping via Neural Bipartite Graph Matching

no code implementations CVPR 2022 Kai Ye, Siyan Dong, Qingnan Fan, He Wang, Li Yi, Fei Xia, Jue Wang, Baoquan Chen

Previous approaches either choose the frontier as the goal position via a myopic solution that hinders the time efficiency, or maximize the long-term value via reinforcement learning to directly regress the goal position, but does not guarantee the complete map construction.

Graph Matching reinforcement-learning +1

FisherMatch: Semi-Supervised Rotation Regression via Entropy-based Filtering

no code implementations CVPR 2022 Yingda Yin, Yingcheng Cai, He Wang, Baoquan Chen

Inspired by the popular semi-supervised approach, FixMatch, we propose to leverage pseudo label filtering to facilitate the information flow from labeled data to unlabeled data in a teacher-student mutual learning framework.

Pseudo Label regression

iPLAN: Interactive and Procedural Layout Planning

1 code implementation CVPR 2022 Feixiang He, Yanlong Huang, He Wang

However, the capability of involving humans into the loop has been largely ignored in existing methods which are mostly end-to-end approaches.

Image Generation Layout Design

CodedVTR: Codebook-based Sparse Voxel Transformer with Geometric Guidance

no code implementations CVPR 2022 Tianchen Zhao, Niansong Zhang, Xuefei Ning, He Wang, Li Yi, Yu Wang

We propose CodedVTR (Codebook-based Voxel TRansformer), which improves data efficiency and generalization ability for 3D sparse voxel transformers.

3D Semantic Segmentation

Defending Black-box Skeleton-based Human Activity Classifiers

2 code implementations9 Mar 2022 He Wang, Yunfeng Diao, Zichang Tan, Guodong Guo

Our method is featured by full Bayesian treatments of the clean data, the adversaries and the classifier, leading to (1) a new Bayesian Energy-based formulation of robust discriminative classifiers, (2) a new adversary sampling scheme based on natural motion manifolds, and (3) a new post-train Bayesian strategy for black-box defense.

Human Activity Recognition Time Series

Learning Category-Level Generalizable Object Manipulation Policy via Generative Adversarial Self-Imitation Learning from Demonstrations

1 code implementation4 Mar 2022 Hao Shen, Weikang Wan, He Wang

Generalizable object manipulation skills are critical for intelligent and multi-functional robots to work in real-world complex scenes.

Imitation Learning

PartAfford: Part-level Affordance Discovery from 3D Objects

no code implementations28 Feb 2022 Chao Xu, Yixin Chen, He Wang, Song-Chun Zhu, Yixin Zhu, Siyuan Huang

We propose a novel learning framework for PartAfford, which discovers part-level representations by leveraging only the affordance set supervision and geometric primitive regularization, without dense supervision.

Pose Guided Image Generation from Misaligned Sources via Residual Flow Based Correction

no code implementations2 Feb 2022 Jiawei Lu, He Wang, Tianjia Shao, Yin Yang, Kun Zhou

However, as source images are often misaligned due to the large disparities among the camera settings, strong assumptions have been made in the past with respect to the camera(s) or/and the object in interest, limiting the application of such techniques.

Pose-Guided Image Generation

Fine-grained differentiable physics: a yarn-level model for fabrics

1 code implementation ICLR 2022 Deshan Gong, Zhanxing Zhu, Andrew J. Bulpitt, He Wang

To this end, we propose several differentiable forces, whose counterparts in empirical physics are indifferentiable, to facilitate gradient-based learning.

ADeLA: Automatic Dense Labeling With Attention for Viewpoint Shift in Semantic Segmentation

no code implementations CVPR 2022 Hanxiang Ren, Yanchao Yang, He Wang, Bokui Shen, Qingnan Fan, Youyi Zheng, C. Karen Liu, Leonidas J. Guibas

We describe a method to deal with performance drop in semantic segmentation caused by viewpoint changes within multi-camera systems, where temporally paired images are readily available, but the annotations may only be abundant for a few typical views.

Semantic Segmentation Unsupervised Domain Adaptation

Domain Adaptation on Point Clouds via Geometry-Aware Implicits

no code implementations CVPR 2022 Yuefan Shen, Yanchao Yang, Mi Yan, He Wang, Youyi Zheng, Leonidas Guibas

Here we propose a simple yet effective method for unsupervised domain adaptation on point clouds by employing a self-supervised task of learning geometry-aware implicits, which plays two critical roles in one shot.

Autonomous Driving Unsupervised Domain Adaptation

Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network

1 code implementation17 Dec 2021 An Tao, Yueqi Duan, He Wang, Ziyi Wu, Pengliang Ji, Haowen Sun, Jie zhou, Jiwen Lu

It results in a serious issue of lagged gradient, making the learned attack at the current step ineffective due to the architecture changes afterward.

3D Classification 3D Semantic Segmentation +1

Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation

no code implementations NeurIPS 2021 Xiaolong Li, Yijia Weng, Li Yi, Leonidas Guibas, A. Lynn Abbott, Shuran Song, He Wang

Category-level object pose estimation aims to find 6D object poses of previously unseen object instances from known categories without access to object CAD models.

Pose Estimation Self-Supervised Learning

Unsupervised Image Generation with Infinite Generative Adversarial Networks

1 code implementation ICCV 2021 Hui Ying, He Wang, Tianjia Shao, Yin Yang, Kun Zhou

Image generation has been heavily investigated in computer vision, where one core research challenge is to generate images from arbitrarily complex distributions with little supervision.

Image Generation

ADeLA: Automatic Dense Labeling with Attention for Viewpoint Adaptation in Semantic Segmentation

1 code implementation29 Jul 2021 Yanchao Yang, Hanxiang Ren, He Wang, Bokui Shen, Qingnan Fan, Youyi Zheng, C. Karen Liu, Leonidas Guibas

Furthermore, to resolve ambiguities in converting the semantic images to semantic labels, we treat the view transformation network as a functional representation of an unknown mapping implied by the color images and propose functional label hallucination to generate pseudo-labels in the target domain.

Inductive Bias Semantic Segmentation +1

Survey of Image Based Graph Neural Networks

no code implementations11 Jun 2021 Usman Nazir, He Wang, Murtaza Taj

In this survey paper, we analyze image based graph neural networks and propose a three-step classification approach.

Classification Superpixels

Leveraging SE(3) Equivariance for Self-supervised Category-Level Object Pose Estimation from Point Clouds

no code implementations NeurIPS 2021 Xiaolong Li, Yijia Weng, Li Yi, Leonidas Guibas, A. Lynn Abbott, Shuran Song, He Wang

To reduce the huge amount of pose annotations needed for category-level learning, we propose for the first time a self-supervised learning framework to estimate category-level 6D object pose from single 3D point clouds.

Pose Estimation Self-Supervised Learning

Maneuver-based Anchor Trajectory Hypotheses at Roundabouts

1 code implementation22 Apr 2021 Mohamed Hasan, Evangelos Paschalidis, Albert Solernou, He Wang, Gustav Markkula, Richard Romano

Accordingly, our model employs a set of maneuver-specific anchor trajectories that cover the space of possible outcomes at the roundabout.

motion prediction Navigate

CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds

1 code implementation ICCV 2021 Yijia Weng, He Wang, Qiang Zhou, Yuzhe Qin, Yueqi Duan, Qingnan Fan, Baoquan Chen, Hao Su, Leonidas J. Guibas

For the first time, we propose a unified framework that can handle 9DoF pose tracking for novel rigid object instances as well as per-part pose tracking for articulated objects from known categories.

Pose Tracking

Decentralized Statistical Inference with Unrolled Graph Neural Networks

1 code implementation4 Apr 2021 He Wang, Yifei Shen, Ziyuan Wang, Dongsheng Li, Jun Zhang, Khaled B. Letaief, Jie Lu

In this paper, we investigate the decentralized statistical inference problem, where a network of agents cooperatively recover a (structured) vector from private noisy samples without centralized coordination.

Data-Driven Optimization for Atlanta Police Zone Design

no code implementations30 Mar 2021 Shixiang Zhu, He Wang, Yao Xie

By analyzing data before and after the zone redesign, we show that the new design has reduced the response time to high priority 911 calls by 5. 8\% and the imbalance of police workload among different zones by 43\%.

BASAR:Black-box Attack on Skeletal Action Recognition

1 code implementation CVPR 2021 Yunfeng Diao, Tianjia Shao, Yong-Liang Yang, Kun Zhou, He Wang

The robustness of skeleton-based activity recognizers has been questioned recently, which shows that they are vulnerable to adversarial attacks when the full-knowledge of the recognizer is accessible to the attacker.

Action Recognition Adversarial Attack +1

Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack

1 code implementation CVPR 2021 He Wang, Feixiang He, Zhexi Peng, Tianjia Shao, Yong-Liang Yang, Kun Zhou, David Hogg

In this paper, we examine the robustness of state-of-the-art action recognizers against adversarial attack, which has been rarely investigated so far.

Action Recognition Adversarial Attack +3

Enhanced 3D Human Pose Estimation from Videos by using Attention-Based Neural Network with Dilated Convolutions

1 code implementation4 Mar 2021 Ruixu Liu, Ju Shen, He Wang, Chen Chen, Sen-ching Cheung, Vijayan K. Asari

In this work, we show a systematic design (from 2D to 3D) for how conventional networks and other forms of constraints can be incorporated into the attention framework for learning long-range dependencies for the task of pose estimation.

3D Human Pose Estimation

Distributed Optimization with Coupling Constraints

no code implementations25 Feb 2021 Xuyang Wu, He Wang, Jie Lu

In this paper, we develop a novel distributed algorithm for addressing convex optimization with both nonlinear inequality and linear equality constraints, where the objective function can be a general nonsmooth convex function and all the constraints can be fully coupled.

Distributed Optimization Optimization and Control

High-order Differentiable Autoencoder for Nonlinear Model Reduction

no code implementations19 Feb 2021 Siyuan Shen, Yang Yin, Tianjia Shao, He Wang, Chenfanfu Jiang, Lei Lan, Kun Zhou

This paper provides a new avenue for exploiting deep neural networks to improve physics-based simulation.

In-game Residential Home Planning via Visual Context-aware Global Relation Learning

no code implementations8 Feb 2021 Lijuan Liu, Yin Yang, Yi Yuan, Tianjia Shao, He Wang, Kun Zhou

In this paper, we propose an effective global relation learning algorithm to recommend an appropriate location of a building unit for in-game customization of residential home complex.

Graph Generation

MoDL-QSM: Model-based Deep Learning for Quantitative Susceptibility Mapping

1 code implementation21 Jan 2021 Ruimin Feng, Jiayi Zhao, He Wang, Baofeng Yang, Jie Feng, Yuting Shi, Ming Zhang, Chunlei Liu, Yuyao Zhang, Jie Zhuang, Hongjiang Wei

However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label.


Systematic electrochemical etching of various metal tips for tunneling spectroscopy and scanning probe microscopy

no code implementations18 Jan 2021 Jiawei Zhang, Pinyuan Wang, Xuao Zhang, Haoran Ji, Jiawei Luo, He Wang, Jian Wang

To ensure the reproducibility of experimental results, the fabrication of tips should be standardized, and a controllable and convenient system should be set up.

Materials Science

MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization

1 code implementation CVPR 2021 Jiahui Huang, He Wang, Tolga Birdal, Minhyuk Sung, Federica Arrigoni, Shi-Min Hu, Leonidas Guibas

We present MultiBodySync, a novel, end-to-end trainable multi-body motion segmentation and rigid registration framework for multiple input 3D point clouds.

Motion Estimation Motion Segmentation

Single Image 3D Shape Retrieval via Cross-Modal Instance and Category Contrastive Learning

no code implementations ICCV 2021 Ming-Xian Lin, Jie Yang, He Wang, Yu-Kun Lai, Rongfei Jia, Binqiang Zhao, Lin Gao

Inspired by the great success in recent contrastive learning works on self-supervised representation learning, we propose a novel IBSR pipeline leveraging contrastive learning.

3D Shape Retrieval Contrastive Learning +4

Detection of magnetic gap in the topological surface states of MnBi2Te4

no code implementations31 Dec 2020 Haoran Ji, Yanzhao Liu, He Wang, Jiawei Luo, Jiaheng Li, Hao Li, Yang Wu, Yong Xu, Jian Wang

An essential ingredient to realize these quantum states is the magnetic gap in the topological surface states induced by the out-of-plane ferromagnetism on the surface of MnBi2Te4.

Materials Science

3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection

2 code implementations CVPR 2021 He Wang, Yezhen Cong, Or Litany, Yue Gao, Leonidas J. Guibas

On KITTI, we are the first to demonstrate semi-supervised 3D object detection and our method surpasses a fully supervised baseline from 1. 8% to 7. 6% under different label ratios and categories.

3D Object Detection Autonomous Driving +1

IF-Defense: 3D Adversarial Point Cloud Defense via Implicit Function based Restoration

2 code implementations11 Oct 2020 Ziyi Wu, Yueqi Duan, He Wang, Qingnan Fan, Leonidas J. Guibas

The former aims to recover the surface of point cloud through implicit function, while the latter encourages evenly-distributed points.

Constant Regret Re-solving Heuristics for Price-based Revenue Management

no code implementations7 Sep 2020 Yining Wang, He Wang

First, we prove that a natural re-solving heuristic attains $O(1)$ regret compared to the value of the optimal policy.


Dynamic Future Net: Diversified Human Motion Generation

no code implementations25 Aug 2020 Wenheng Chen, He Wang, Yi Yuan, Tianjia Shao, Kun Zhou

We evaluate our model on a wide range of motions and compare it with the state-of-the-art methods.

Object-Centric Multi-View Aggregation

no code implementations20 Jul 2020 Shubham Tulsiani, Or Litany, Charles R. Qi, He Wang, Leonidas J. Guibas

We present an approach for aggregating a sparse set of views of an object in order to compute a semi-implicit 3D representation in the form of a volumetric feature grid.

Novel View Synthesis Pose Estimation

Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data

no code implementations14 Jun 2020 Bing Yu, Ke Sun, He Wang, Zhouchen Lin, Zhanxing Zhu

In particular, we present a novel training framework to jointly target both PU classification and conditional generation when exposing to extra data, especially out-of-distribution unlabeled data, by exploring the interplay between them: 1) enhancing the performance of PU classifiers with the assistance of a novel Conditional Generative Adversarial Network~(CGAN) that is robust to noisy labels, 2) leveraging extra data with predicted labels from a PU classifier to help the generation.

Classification General Classification

Rethinking Sampling in 3D Point Cloud Generative Adversarial Networks

no code implementations12 Jun 2020 He Wang, Zetian Jiang, Li Yi, Kaichun Mo, Hao Su, Leonidas J. Guibas

We further study how different evaluation metrics weigh the sampling pattern against the geometry and propose several perceptual metrics forming a sampling spectrum of metrics.

Informative Scene Decomposition for Crowd Analysis, Comparison and Simulation Guidance

no code implementations29 Apr 2020 Feixiang He, Yuanhang Xiang, Xi Zhao, He Wang

The method takes as input raw and noisy data with highly mixed multi-dimensional (space, time and dynamics) information, and automatically structure it by learning the correlations among these dimensions.

Data Visualization

MeshingNet: A New Mesh Generation Method based on Deep Learning

no code implementations15 Apr 2020 Zheyan Zhang, Yongxing Wang, Peter K. Jimack, He Wang

The framework that we have developed is based around training an artificial neural network (ANN) to guide standard mesh generation software, based upon a prediction of the required local mesh density throughout the domain.

SAPIEN: A SimulAted Part-based Interactive ENvironment

1 code implementation CVPR 2020 Fanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia, Hao Zhu, Fangchen Liu, Minghua Liu, Hanxiao Jiang, Yifu Yuan, He Wang, Li Yi, Angel X. Chang, Leonidas J. Guibas, Hao Su

To achieve this task, a simulated environment with physically realistic simulation, sufficient articulated objects, and transferability to the real robot is indispensable.

Curriculum DeepSDF

1 code implementation ECCV 2020 Yueqi Duan, Haidong Zhu, He Wang, Li Yi, Ram Nevatia, Leonidas J. Guibas

When learning to sketch, beginners start with simple and flexible shapes, and then gradually strive for more complex and accurate ones in the subsequent training sessions.

3D Shape Representation Representation Learning

PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions

1 code implementation ECCV 2020 Kaichun Mo, He Wang, Xinchen Yan, Leonidas J. Guibas

3D generative shape modeling is a fundamental research area in computer vision and interactive computer graphics, with many real-world applications.

3D Shape Generation

Human-like Planning for Reaching in Cluttered Environments

1 code implementation28 Feb 2020 Mohamed Hasan, Matthew Warburton, Wisdom C. Agboh, Mehmet R. Dogar, Matteo Leonetti, He Wang, Faisal Mushtaq, Mark Mon-Williams, Anthony G. Cohn

From this, we devised a qualitative representation of the task space to abstract the decision making, irrespective of the number of obstacles.

Decision Making

Predicting the Physical Dynamics of Unseen 3D Objects

1 code implementation16 Jan 2020 Davis Rempe, Srinath Sridhar, He Wang, Leonidas J. Guibas

Experiments show that we can accurately predict the changes in state for unseen object geometries and initial conditions.

Category-Level Articulated Object Pose Estimation

2 code implementations CVPR 2020 Xiaolong Li, He Wang, Li Yi, Leonidas Guibas, A. Lynn Abbott, Shuran Song

We develop a deep network based on PointNet++ that predicts ANCSH from a single depth point cloud, including part segmentation, normalized coordinates, and joint parameters in the canonical object space.

Pose Estimation

SMART: Skeletal Motion Action Recognition aTtack

no code implementations16 Nov 2019 He Wang, Feixiang He, Zhexi Peng, Yong-Liang Yang, Tianjia Shao, Kun Zhou, David Hogg

In this paper, we propose a method, SMART, to attack action recognizers which rely on 3D skeletal motions.

Action Recognition Adversarial Attack +1

Gravitational wave signal recognition of O1 data by deep learning

1 code implementation30 Sep 2019 He Wang, Zhoujian Cao, Xiaolin Liu, Shichao Wu, Jian-Yang Zhu

Our adjusted convolutional neural network admits comparable accuracy and efficiency of signal recognition as other deep learning works published in the literature.

Instrumentation and Methods for Astrophysics General Relativity and Quantum Cosmology

Spatio-temporal Manifold Learning for Human Motions via Long-horizon Modeling

no code implementations20 Aug 2019 He Wang, Edmond S. L. Ho, Hubert P. H. Shum, Zhanxing Zhu

In this paper, we propose a new deep network to tackle these challenges by creating a natural motion manifold that is versatile for many applications.

Denoising Time Series

Competing Against Equilibria in Zero-Sum Games with Evolving Payoffs

1 code implementation17 Jul 2019 Adrian Rivera Cardoso, Jacob Abernethy, He Wang, Huan Xu

Finding the Nash Equilibrium (NE) of a two player zero-sum game is core to many problems in statistics, optimization, and economics, and for a fixed game matrix this can be easily reduced to solving a linear program.

Large Scale Markov Decision Processes with Changing Rewards

no code implementations NeurIPS 2019 Adrian Rivera Cardoso, He Wang, Huan Xu

We consider Markov Decision Processes (MDPs) where the rewards are unknown and may change in an adversarial manner.

DADA-2000: Can Driving Accident be Predicted by Driver Attention? Analyzed by A Benchmark

no code implementations23 Apr 2019 Jianwu Fang, Dingxin Yan, Jiahuan Qiao, Jianru Xue, He Wang, Sen Li

Driver attention prediction is currently becoming the focus in safe driving research community, such as the DR(eye)VE project and newly emerged Berkeley DeepDrive Attention (BDD-A) database in critical situations.

Driver Attention Monitoring

Learning Generalizable Physical Dynamics of 3D Rigid Objects

no code implementations2 Jan 2019 Davis Rempe, Srinath Sridhar, He Wang, Leonidas J. Guibas

In this work, we focus on predicting the dynamics of 3D rigid objects, in particular an object's final resting position and total rotation when subjected to an impulsive force.

Autonomous Vehicles

Globally Continuous and Non-Markovian Activity Analysis from Videos

no code implementations11 Oct 2018 He Wang, Carol O'Sullivan

By combining these patterns with detailed environment information, we interpret the semantics of activities and report anomalies.

Novelty Detection Meets Collider Physics

no code implementations26 Jul 2018 Jan Hajer, Ying-Ying Li, Tao Liu, He Wang

Complementary to supervised learning, it allows to analyze data model-independently.

The Online Saddle Point Problem and Online Convex Optimization with Knapsacks

no code implementations21 Jun 2018 Adrian Rivera, He Wang, Huan Xu

We relate this problem to the online saddle point problem and establish $O(\sqrt{T})$ regret using a primal-dual algorithm.

“Congruent” and “Opposite” Neurons: Sisters for Multisensory Integration and Segregation

no code implementations NeurIPS 2016 Wen-Hao Zhang, He Wang, K. Y. Michael Wong, Si Wu

Mimicking the experimental protocol, our model reproduces the characteristics of congruent and opposite neurons, and demonstrates that in each module, the sisters of congruent and opposite neurons can jointly achieve optimal multisensory information integration and segregation.

Saliency Detection via Cellular Automata

no code implementations CVPR 2015 Yao Qin, Huchuan Lu, Yiqun Xu, He Wang

In this paper, we introduce Cellular Automata--a dynamic evolution model to intuitively detect the salient object.

Saliency Detection

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