4 code implementations • ECCV 2018 • Weiyue Wang, Ulrich Neumann
Convolutional neural networks (CNN) are limited by the lack of capability to handle geometric information due to the fixed grid kernel structure.
Ranked #6 on Semantic Segmentation on Stanford2D3D - RGBD
3 code implementations • NeurIPS 2019 • Qiangeng Xu, Weiyue Wang, Duygu Ceylan, Radomir Mech, Ulrich Neumann
Reconstructing 3D shapes from single-view images has been a long-standing research problem.
Ranked #1 on Single-View 3D Reconstruction on ShapeNetCore
1 code implementation • CVPR 2018 • Weiyue Wang, Ronald Yu, Qiangui Huang, Ulrich Neumann
Experimental results on various 3D scenes show the effectiveness of our method on 3D instance segmentation, and we also evaluate the capability of SGPN to improve 3D object detection and semantic segmentation results.
Ranked #1 on 3D Semantic Instance Segmentation on ScanNetV1
2 code implementations • CVPR 2018 • Qiangui Huang, Weiyue Wang, Ulrich Neumann
The key component of the RSNet is a lightweight local dependency module.
Ranked #46 on Semantic Segmentation on S3DIS
1 code implementation • CVPR 2019 • Weiyue Wang, Duygu Ceylan, Radomir Mech, Ulrich Neumann
Given such a source 3D model and a target which can be a 2D image, 3D model, or a point cloud acquired as a depth scan, we introduce 3DN, an end-to-end network that deforms the source model to resemble the target.
1 code implementation • ICCV 2017 • Weiyue Wang, Qiangui Huang, Suya You, Chao Yang, Ulrich Neumann
The 3D-ED-GAN is a 3D convolutional neural network trained with a generative adversarial paradigm to fill missing 3D data in low-resolution.
1 code implementation • IJCNLP 2019 • Yingbo Gao, Weiyue Wang, Hermann Ney
The preprocessing pipelines in Natural Language Processing usually involve a step of removing sentences consisted of illegal characters.
no code implementations • 22 Nov 2016 • Qiangui Huang, Weiyue Wang, Kevin Zhou, Suya You, Ulrich Neumann
A novel neural network architecture is built for scene labeling tasks where one of the variants of the new RNN unit, Gated Recurrent Unit with Explicit Long-range Conditioning (GRU-ELC), is used to model multi scale contextual dependencies in images.
no code implementations • 16 Feb 2016 • Weiyao Lin, Yang Mi, Weiyue Wang, Jianxin Wu, Jingdong Wang, Tao Mei
These semantic regions can be used to recognize pre-defined activities in crowd scenes.
no code implementations • 1 Sep 2018 • Qiangeng Xu, Hanwang Zhang, Weiyue Wang, Peter N. Belhumeur, Ulrich Neumann
In this paper, we introduce a stochastic dynamics video infilling (SDVI) framework to generate frames between long intervals in a video.
no code implementations • ACL 2018 • Weiyue Wang, Derui Zhu, Tamer Alkhouli, Zixuan Gan, Hermann Ney
Attention-based neural machine translation (NMT) models selectively focus on specific source positions to produce a translation, which brings significant improvements over pure encoder-decoder sequence-to-sequence models.
no code implementations • ACL 2017 • Weiyue Wang, Tamer Alkhouli, Derui Zhu, Hermann Ney
Recently, the neural machine translation systems showed their promising performance and surpassed the phrase-based systems for most translation tasks.
no code implementations • WS 2019 • Jan Rosendahl, Christian Herold, Yunsu Kim, Miguel Gra{\c{c}}a, Weiyue Wang, Parnia Bahar, Yingbo Gao, Hermann Ney
For the De-En task, none of the tested methods gave a significant improvement over last years winning system and we end up with the same performance, resulting in 39. 6{\%} BLEU on newstest2019.
no code implementations • WS 2019 • Peter Stanchev, Weiyue Wang, Hermann Ney
Over the years a number of machine translation metrics have been developed in order to evaluate the accuracy and quality of machine-generated translations.
no code implementations • EMNLP (IWSLT) 2019 • Yingbo Gao, Christian Herold, Weiyue Wang, Hermann Ney
Prominently used in support vector machines and logistic regressions, kernel functions (kernels) can implicitly map data points into high dimensional spaces and make it easier to learn complex decision boundaries.
no code implementations • 20 May 2020 • Jingjing Huo, Yingbo Gao, Weiyue Wang, Ralf Schlüter, Hermann Ney
After that, we apply the best norm-scaling setup in combination with various margins and conduct neural language models rescoring experiments in automatic speech recognition.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Yingbo Gao, Weiyue Wang, Christian Herold, Zijian Yang, Hermann Ney
In order to combat overfitting and in pursuit of better generalization, label smoothing is widely applied in modern neural machine translation systems.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Zijian Yang, Yingbo Gao, Weiyue Wang, Hermann Ney
Attention-based encoder-decoder models have achieved great success in neural machine translation tasks.
no code implementations • CVPR 2021 • Pei Sun, Weiyue Wang, Yuning Chai, Gamaleldin Elsayed, Alex Bewley, Xiao Zhang, Cristian Sminchisescu, Dragomir Anguelov
These larger detection ranges require more efficient and accurate detection models.
no code implementations • CVPR 2021 • Yuning Chai, Pei Sun, Jiquan Ngiam, Weiyue Wang, Benjamin Caine, Vijay Vasudevan, Xiao Zhang, Dragomir Anguelov
3D object detection is vital for many robotics applications.
no code implementations • ICCV 2021 • Qiangeng Xu, Yin Zhou, Weiyue Wang, Charles R. Qi, Dragomir Anguelov
On the Waymo Open Dataset and KITTI, SPG improves 3D detection results of these two methods across all categories.
Ranked #5 on 3D Object Detection on KITTI Cars Moderate
no code implementations • ACL 2021 • Weiyue Wang, Zijian Yang, Yingbo Gao, Hermann Ney
The neural hidden Markov model has been proposed as an alternative to attention mechanism in machine translation with recurrent neural networks.
no code implementations • COLING 2020 • Zhihong Lei, Weiyue Wang, Christian Dugast, Hermann Ney
Named entity recognition is a key component in various natural language processing systems, and neural architectures provide significant improvements over conventional approaches.
no code implementations • 27 Sep 2021 • Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang, Pavel Petrushkov, Tomer Lancewicki, Shahram Khadivi, Hermann Ney
Pivot-based neural machine translation (NMT) is commonly used in low-resource setups, especially for translation between non-English language pairs.
no code implementations • ACL (IWSLT) 2021 • Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang, Pavel Petrushkov, Tomer Lancewicki, Shahram Khadivi, Hermann Ney
Complex natural language applications such as speech translation or pivot translation traditionally rely on cascaded models.
no code implementations • ACL 2021 • Evgeniia Tokarchuk, David Thulke, Weiyue Wang, Christian Dugast, Hermann Ney
Data processing is an important step in various natural language processing tasks.
no code implementations • WMT (EMNLP) 2020 • Peter Stanchev, Weiyue Wang, Hermann Ney
An important aspect of machine translation is its evaluation, which can be achieved through the use of a variety of metrics.
no code implementations • EMNLP (IWSLT) 2019 • Jan Rosendahl, Viet Anh Khoa Tran, Weiyue Wang, Hermann Ney
In this work we analyze and compare the behavior of the Transformer architecture when using different positional encoding methods.
no code implementations • 11 May 2022 • Mao Ye, Chenxi Liu, Maoqing Yao, Weiyue Wang, Zhaoqi Leng, Charles R. Qi, Dragomir Anguelov
While multi-class 3D detectors are needed in many robotics applications, training them with fully labeled datasets can be expensive in labeling cost.
no code implementations • 13 Oct 2022 • Pei Sun, Mingxing Tan, Weiyue Wang, Chenxi Liu, Fei Xia, Zhaoqi Leng, Dragomir Anguelov
3D object detection in point clouds is a core component for modern robotics and autonomous driving systems.
no code implementations • 24 Oct 2022 • Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov
To alleviate the cost of hyperparameter tuning and iterative pseudo labeling, we develop a population-based data augmentation framework for 3D detection, named AutoPseudoAugment.
no code implementations • 24 Oct 2022 • Christoph Lüscher, Mohammad Zeineldeen, Zijian Yang, Tina Raissi, Peter Vieting, Khai Le-Duc, Weiyue Wang, Ralf Schlüter, Hermann Ney
Language barriers present a great challenge in our increasingly connected and global world.
no code implementations • 7 Apr 2023 • Kan Chen, Runzhou Ge, Hang Qiu, Rami Ai-Rfou, Charles R. Qi, Xuanyu Zhou, Zoey Yang, Scott Ettinger, Pei Sun, Zhaoqi Leng, Mustafa Baniodeh, Ivan Bogun, Weiyue Wang, Mingxing Tan, Dragomir Anguelov
To study the effect of these modular approaches, design new paradigms that mitigate these limitations, and accelerate the development of end-to-end motion forecasting models, we augment the Waymo Open Motion Dataset (WOMD) with large-scale, high-quality, diverse LiDAR data for the motion forecasting task.