no code implementations • 22 Mar 2023 • Heng Yang, Marco Pavone
Geometric uncertainty propagation, on the other, propagates the geometric constraints on the keypoints to the 6D object pose, leading to a Pose UnceRtainty SEt (PURSE) that guarantees coverage of the groundtruth pose with the same probability.
no code implementations • 24 Jan 2023 • Xiao He, Mingrui Zhu, Nannan Wang, Xinbo Gao, Heng Yang
To address this issue, we propose a novel font generation approach by learning the Difference between different styles and the Similarity of the same style (DS-Font).
1 code implementation • NIPS 2022 • De Cheng, Yixiong Ning, Nannan Wang, Xinbo Gao, Heng Yang, Yuxuan Du, Bo Han, Tongliang Liu
We show that the cycle-consistency regularization helps to minimize the volume of the transition matrix T indirectly without exploiting the estimated noisy class posterior, which could further encourage the estimated transition matrix T to converge to its optimal solution.
1 code implementation • 6 Oct 2022 • Heng Yang, Ke Li
Our study shows that even employing pre-trained language models, existing text augmentation methods generate numerous low-quality instances and lead to the feature space shift problem in augmentation instances.
2 code implementations • 2 Aug 2022 • Heng Yang, Ke Li
The advancement of aspect-based sentiment analysis (ABSA) has urged the lack of a user-friendly framework that can largely lower the difficulty of reproducing state-of-the-art ABSA performance, especially for beginners.
no code implementations • 24 Jun 2022 • Jingnan Shi, Heng Yang, Luca Carlone
We consider an active shape model, where -- for an object category -- we are given a library of potential CAD models describing objects in that category, and we adopt a standard formulation where pose and shape are estimated from 2D or 3D keypoints via non-convex optimization.
1 code implementation • 12 Jun 2022 • Ke Li, Heng Yang, Willem Visser
In this paper, we propose DaNuoYi, an automatic injection testing tool that simultaneously generates test inputs for multiple types of injection attacks on a WAF.
1 code implementation • 16 Oct 2021 • Heng Yang, Ke Li
Compared to existing methods, LSA is an efficient approach that learns the implicit sentiments in a local sentiment aggregation window, which tackles the efficiency problem and avoids the token-node alignment problem of syntax-based methods.
Aspect-Based Sentiment Analysis (ABSA) Sentiment Classification +1
2 code implementations • 7 Sep 2021 • Heng Yang, Luca Carlone
Our third contribution is to solve the SDP relaxations at an unprecedented scale and accuracy by presenting STRIDE, a solver that blends global descent on the convex SDP with fast local search on the nonconvex POP.
no code implementations • 9 Jun 2021 • Baoyun Peng, Min Liu, Heng Yang, Zhaoning Zhang, Dongsheng Li
Based on the proposed quality measurement, we propose a deep Tiny Face Quality network (tinyFQnet) to learn a quality prediction function from data.
1 code implementation • 28 May 2021 • Heng Yang, Ling Liang, Luca Carlone, Kim-Chuan Toh
In particular, we first design a globally convergent inexact projected gradient method (iPGM) for solving the SDP that serves as the backbone of our framework.
no code implementations • 16 Apr 2021 • Jingnan Shi, Heng Yang, Luca Carlone
Our first contribution is to provide the first certifiably optimal solver for pose and shape estimation.
1 code implementation • ICCV 2021 • Heng Yang, Chris Doran, Jean-Jacques Slotine
We study the problem of aligning two sets of 3D geometric primitives given known correspondences.
2 code implementations • CVPR 2021 • Heng Yang, Wei Dong, Luca Carlone, Vladlen Koltun
We present self-supervised geometric perception (SGP), the first general framework to learn a feature descriptor for correspondence matching without any ground-truth geometric model labels (e. g., camera poses, rigid transformations).
no code implementations • 7 Nov 2020 • Jingnan Shi, Heng Yang, Luca Carlone
We also show that in practice the maximum k-core of the compatibility graph provides an approximation of the maximum clique, while being faster to compute in large problems.
2 code implementations • 2 Oct 2020 • Heng Yang, Biqing Zeng
Target-oriented sentiment classification is a fine-grained task of natural language processing to analyze the sentiment polarity of the targets.
no code implementations • 29 Jul 2020 • Pasquale Antonante, Vasileios Tzoumas, Heng Yang, Luca Carlone
We extend ADAPT and GNC to the case where the user does not have prior knowledge of the inlier-noise statistics (or the statistics may vary over time) and is unable to guess a reasonable threshold to separate inliers from outliers (as the one commonly used in RANSAC).
1 code implementation • NeurIPS 2020 • Heng Yang, Luca Carlone
We propose the first general and practical framework to design certifiable algorithms for robust geometric perception in the presence of a large amount of outliers.
no code implementations • 7 May 2020 • Heng Yang
We provide a dynamical perspective on the classical problem of 3D point cloud registration with correspondences.
5 code implementations • 21 Jan 2020 • Heng Yang, Jingnan Shi, Luca Carlone
We propose the first fast and certifiable algorithm for the registration of two sets of 3D points in the presence of large amounts of outlier correspondences.
5 code implementations • 17 Dec 2019 • Heng Yang, Biqing Zeng, JianHao Yang, Youwei Song, Ruyang Xu
Aspect-based sentiment analysis (ABSA) task is a multi-grained task of natural language processing and consists of two subtasks: aspect term extraction (ATE) and aspect polarity classification (APC).
Ranked #3 on Aspect-Based Sentiment Analysis (ABSA) on SemEval 2014 Task 4 Sub Task 2 (using extra training data)
Aspect-Based Sentiment Analysis (ABSA) General Classification +2
no code implementations • CVPR 2020 • Heng Yang, Luca Carlone
We study the problem of 3D shape reconstruction from 2D landmarks extracted in a single image.
4 code implementations • 18 Sep 2019 • Heng Yang, Pasquale Antonante, Vasileios Tzoumas, Luca Carlone
In this paper, we enable the simultaneous use of non-minimal solvers and robust estimation by providing a general-purpose approach for robust global estimation, which can be applied to any problem where a non-minimal solver is available for the outlier-free case.
4 code implementations • ICCV 2019 • Heng Yang, Luca Carlone
Our first contribution is to formulate the Wahba problem using a Truncated Least Squares (TLS) cost that is insensitive to a large fraction of spurious correspondences.
2 code implementations • 20 Mar 2019 • Heng Yang, Luca Carlone
We propose a robust approach for the registration of two sets of 3D points in the presence of a large amount of outliers.
no code implementations • 14 Jun 2018 • Huiyuan Zhuo, Xuelin Qian, Yanwei Fu, Heng Yang, xiangyang xue
In this paper, we proposed a novel filter pruning for convolutional neural networks compression, namely spectral clustering filter pruning with soft self-adaption manners (SCSP).
no code implementations • 17 Apr 2018 • Jiaolong Xu, Peng Wang, Heng Yang, Antonio M. López
Autonomous driving has harsh requirements of small model size and energy efficiency, in order to enable the embedded system to achieve real-time on-board object detection.
no code implementations • 16 Nov 2015 • Heng Yang, Xuhui Jia, Chen Change Loy, Peter Robinson
In this paper, we carry out a rigorous evaluation of these methods by making the following contributions: 1) we proposes a new evaluation metric for face alignment on a set of images, i. e., area under error distribution curve within a threshold, AUC$_\alpha$, given the fact that the traditional evaluation measure (mean error) is very sensitive to big alignment error.
no code implementations • 16 Sep 2015 • Heng Yang, Renqiao Zhang, Peter Robinson
Furthermore, we study the impact of training data imbalance on model performance and propose a training sample augmentation scheme that produces more initialisations for training samples from the minority.
1 code implementation • 11 Jul 2015 • Heng Yang, Wenxuan Mou, Yichi Zhang, Ioannis Patras, Hatice Gunes, Peter Robinson
In this paper we propose a supervised initialization scheme for cascaded face alignment based on explicit head pose estimation.
no code implementations • CVPR 2015 • Heng Yang, Ioannis Patras
Our experiments lead to several interesting findings: 1) Surprisingly, most of state of the art methods struggle to preserve the mirror symmetry, despite the fact that they do have very similar overall performance on the original and mirror images; 2) the low mirrorability is not caused by training or testing sample bias - all algorithms are trained on both the original images and their mirrored versions; 3) the mirror error is strongly correlated to the localization/alignment error (with correlation coefficients around 0. 7).
no code implementations • CVPR 2014 • Changqing Zou, Heng Yang, Jianzhuang Liu
Reconstructing 3D objects from single line drawings is often desirable in computer vision and graphics applications.