Search Results for author: Hao Tang

Found 154 papers, 81 papers with code

GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis

1 code implementation30 Jan 2023 Ming Tao, Bing-Kun Bao, Hao Tang, Changsheng Xu

The complex scene understanding ability of CLIP enables the discriminator to accurately assess the image quality.

Image Generation Scene Understanding

Bipartite Graph Diffusion Model for Human Interaction Generation

no code implementations24 Jan 2023 Baptiste Chopin, Hao Tang, Mohamed Daoudi

The generation of natural human motion interactions is a hot topic in computer vision and computer animation.

Few-shot Medical Image Segmentation with Cycle-resemblance Attention

no code implementations7 Dec 2022 Hao Ding, Changchang Sun, Hao Tang, Dawen Cai, Yan Yan

Recently, due to the increasing requirements of medical imaging applications and the professional requirements of annotating medical images, few-shot learning has gained increasing attention in the medical image semantic segmentation field.

Few-Shot Learning Image Segmentation +2

Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training

1 code implementation19 Nov 2022 Zhenglun Kong, Haoyu Ma, Geng Yuan, Mengshu Sun, Yanyue Xie, Peiyan Dong, Xin Meng, Xuan Shen, Hao Tang, Minghai Qin, Tianlong Chen, Xiaolong Ma, Xiaohui Xie, Zhangyang Wang, Yanzhi Wang

Vision transformers (ViTs) have recently obtained success in many applications, but their intensive computation and heavy memory usage at both training and inference time limit their generalization.

MelHuBERT: A simplified HuBERT on Mel spectrogram

no code implementations17 Nov 2022 Tzu-Quan Lin, Hung-Yi Lee, Hao Tang

Self-supervised models have had great success in learning speech representations that can generalize to various downstream tasks.

Compressing Transformer-based self-supervised models for speech processing

no code implementations17 Nov 2022 Tzu-Quan Lin, Tsung-Huan Yang, Chun-Yao Chang, Kuang-Ming Chen, Tzu-hsun Feng, Hung-Yi Lee, Hao Tang

Despite the success of Transformers in self-supervised learning with applications to various downstream tasks, the computational cost of training and inference remains a major challenge for applying these models to a wide spectrum of devices.

Knowledge Distillation Self-Supervised Learning

Bipartite Graph Reasoning GANs for Person Pose and Facial Image Synthesis

1 code implementation12 Nov 2022 Hao Tang, Ling Shao, Philip H. S. Torr, Nicu Sebe

To further capture the change in pose of each part more precisely, we propose a novel part-aware bipartite graph reasoning (PBGR) block to decompose the task of reasoning the global structure transformation with a bipartite graph into learning different local transformations for different semantic body/face parts.

Image Generation

Deep Unsupervised Key Frame Extraction for Efficient Video Classification

no code implementations12 Nov 2022 Hao Tang, Lei Ding, Songsong Wu, Bin Ren, Nicu Sebe, Paolo Rota

The proposed TSDPC is a generic and powerful framework and it has two advantages compared with previous works, one is that it can calculate the number of key frames automatically.

Classification Video Classification

The Lottery Ticket Hypothesis for Vision Transformers

no code implementations2 Nov 2022 Xuan Shen, Zhenglun Kong, Minghai Qin, Peiyan Dong, Geng Yuan, Xin Meng, Hao Tang, Xiaolong Ma, Yanzhi Wang

That is, there exists a subset of input image patches such that a ViT can be trained from scratch by using only this subset of patches and achieve similar accuracy to the ViTs trained by using all image patches.

Informativeness

Learning Dependencies of Discrete Speech Representations with Neural Hidden Markov Models

no code implementations29 Oct 2022 Sung-Lin Yeh, Hao Tang

While discrete latent variable models have had great success in self-supervised learning, most models assume that frames are independent.

Self-Supervised Learning

Analyzing Acoustic Word Embeddings from Pre-trained Self-supervised Speech Models

no code implementations28 Oct 2022 Ramon Sanabria, Hao Tang, Sharon Goldwater

Given the strong results of self-supervised models on various tasks, there have been surprisingly few studies exploring self-supervised representations for acoustic word embeddings (AWE), fixed-dimensional vectors representing variable-length spoken word segments.

Word Embeddings

Conditioning and Sampling in Variational Diffusion Models for Speech Super-Resolution

1 code implementation27 Oct 2022 Chin-Yun Yu, Sung-Lin Yeh, György Fazekas, Hao Tang

Moreover, by coupling the proposed sampling method with an unconditional DM, i. e., a DM with no auxiliary inputs to its noise predictor, we can generalize it to a wide range of SR setups.

Super-Resolution

On Compressing Sequences for Self-Supervised Speech Models

no code implementations13 Oct 2022 Yen Meng, Hsuan-Jui Chen, Jiatong Shi, Shinji Watanabe, Paola Garcia, Hung-Yi Lee, Hao Tang

Subsampling while training self-supervised models not only improves the overall performance on downstream tasks under certain frame rates, but also brings significant speed-up in inference.

Self-Supervised Learning

SiNeRF: Sinusoidal Neural Radiance Fields for Joint Pose Estimation and Scene Reconstruction

1 code implementation10 Oct 2022 Yitong Xia, Hao Tang, Radu Timofte, Luc van Gool

NeRFmm is the Neural Radiance Fields (NeRF) that deal with Joint Optimization tasks, i. e., reconstructing real-world scenes and registering camera parameters simultaneously.

Image Generation Pose Estimation

Boosting Few-shot Fine-grained Recognition with Background Suppression and Foreground Alignment

1 code implementation4 Oct 2022 Zican Zha, Hao Tang, Yunlian Sun, Jinhui Tang

To address this challenging task, we propose a two-stage background suppression and foreground alignment framework, which is composed of a background activation suppression (BAS) module, a foreground object alignment (FOA) module, and a local-to-local (L2L) similarity metric.

Few-Shot Learning

Physical Adversarial Attack meets Computer Vision: A Decade Survey

1 code implementation30 Sep 2022 Hui Wei, Hao Tang, Xuemei Jia, Hanxun Yu, Zhubo Li, Zhixiang Wang, Shin'ichi Satoh, Zheng Wang

Although Deep Neural Networks (DNNs) have achieved impressive results in computer vision, their exposed vulnerability to adversarial attacks remains a serious concern.

Adversarial Attack Medical Diagnosis

PPT: token-Pruned Pose Transformer for monocular and multi-view human pose estimation

1 code implementation16 Sep 2022 Haoyu Ma, Zhe Wang, Yifei Chen, Deying Kong, Liangjian Chen, Xingwei Liu, Xiangyi Yan, Hao Tang, Xiaohui Xie

In this paper, we propose the token-Pruned Pose Transformer (PPT) for 2D human pose estimation, which can locate a rough human mask and performs self-attention only within selected tokens.

 Ranked #1 on 3D Human Pose Estimation on Human3.6M (Using 2D ground-truth joints metric, using extra training data)

3D Human Pose Estimation

Facial Expression Translation using Landmark Guided GANs

1 code implementation5 Sep 2022 Hao Tang, Nicu Sebe

We propose a simple yet powerful Landmark guided Generative Adversarial Network (LandmarkGAN) for the facial expression-to-expression translation using a single image, which is an important and challenging task in computer vision since the expression-to-expression translation is a non-linear and non-aligned problem.

Facial Expression Translation Translation

Image-Specific Information Suppression and Implicit Local Alignment for Text-based Person Search

no code implementations30 Aug 2022 Shuanglin Yan, Hao Tang, Liyan Zhang, Jinhui Tang

Secondly, we propose an implicit local alignment module to adaptively aggregate image and text features to a set of modality-shared semantic topic centers, and implicitly learn the local fine-grained correspondence between images and texts without additional supervision information and complex cross-modal interactions.

Person Search Text based Person Search

Training and Tuning Generative Neural Radiance Fields for Attribute-Conditional 3D-Aware Face Generation

1 code implementation26 Aug 2022 Jichao Zhang, Aliaksandr Siarohin, Yahui Liu, Hao Tang, Nicu Sebe, Wei Wang

To this end, we introduce a conditional GNeRF model that uses specific attribute labels as input in order to improve the controllabilities and disentangling abilities of 3D-aware generative models.

Disentanglement Face Generation

Identity-Sensitive Knowledge Propagation for Cloth-Changing Person Re-identification

1 code implementation25 Aug 2022 Jianbing Wu, Hong Liu, Wei Shi, Hao Tang, Jingwen Guo

To mitigate the resolution degradation issue and mine identity-sensitive cues from human faces, we propose to restore the missing facial details using prior facial knowledge, which is then propagated to a smaller network.

Human Parsing Person Re-Identification

Vector Quantized Diffusion Model with CodeUnet for Text-to-Sign Pose Sequences Generation

no code implementations19 Aug 2022 Pan Xie, Qipeng Zhang, Zexian Li, Hao Tang, Yao Du, Xiaohui Hu

To address this issue, we propose a vector quantized diffusion method for conditional pose sequences generation, called PoseVQ-Diffusion, which is an iterative non-autoregressive method.

Sign Language Production

Auto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization

no code implementations10 Aug 2022 Zhengang Li, Mengshu Sun, Alec Lu, Haoyu Ma, Geng Yuan, Yanyue Xie, Hao Tang, Yanyu Li, Miriam Leeser, Zhangyang Wang, Xue Lin, Zhenman Fang

Compared with state-of-the-art ViT quantization work (algorithmic approach only without hardware acceleration), our quantization achieves 0. 47% to 1. 36% higher Top-1 accuracy under the same bit-width.

Quantization

Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution

1 code implementation25 Jul 2022 Yushu Wu, Yifan Gong, Pu Zhao, Yanyu Li, Zheng Zhan, Wei Niu, Hao Tang, Minghai Qin, Bin Ren, Yanzhi Wang

Instead of measuring the speed on mobile devices at each iteration during the search process, a speed model incorporated with compiler optimizations is leveraged to predict the inference latency of the SR block with various width configurations for faster convergence.

Neural Architecture Search SSIM +1

Towards Interpretable Video Super-Resolution via Alternating Optimization

1 code implementation21 Jul 2022 JieZhang Cao, Jingyun Liang, Kai Zhang, Wenguan Wang, Qin Wang, Yulun Zhang, Hao Tang, Luc van Gool

These issues can be alleviated by a cascade of three separate sub-tasks, including video deblurring, frame interpolation, and super-resolution, which, however, would fail to capture the spatial and temporal correlations among video sequences.

Deblurring Space-time Video Super-resolution +2

MLP-GAN for Brain Vessel Image Segmentation

no code implementations17 Jul 2022 Bin Xie, Hao Tang, Bin Duan, Dawen Cai, Yan Yan

Brain vessel image segmentation can be used as a promising biomarker for better prevention and treatment of different diseases.

Image Segmentation Image-to-Image Translation +1

RCRN: Real-world Character Image Restoration Network via Skeleton Extraction

no code implementations16 Jul 2022 Daqian Shi, Xiaolei Diao, Hao Tang, Xiaomin Li, Hao Xing, Hao Xu

SENet aims to preserve the structural consistency of the character and normalize complex noise.

Image Restoration

CharFormer: A Glyph Fusion based Attentive Framework for High-precision Character Image Denoising

1 code implementation16 Jul 2022 Daqian Shi, Xiaolei Diao, Lida Shi, Hao Tang, Yang Chi, Chuntao Li, Hao Xu

Degraded images commonly exist in the general sources of character images, leading to unsatisfactory character recognition results.

Image Denoising

REZCR: Zero-shot Character Recognition via Radical Extraction

no code implementations12 Jul 2022 Xiaolei Diao, Daqian Shi, Hao Tang, Yanzeng Li, Lei Wu, Hao Xu

In this paper, we propose a zero-shot character recognition framework via radical extraction (REZCR) to improve the recognition performance of few-sample character categories in the tail.

PI-Trans: Parallel-ConvMLP and Implicit-Transformation Based GAN for Cross-View Image Translation

no code implementations9 Jul 2022 Bin Ren, Hao Tang, Yiming Wang, Xia Li, Wei Wang, Nicu Sebe

For semantic-guided cross-view image translation, it is crucial to learn where to sample pixels from the source view image and where to reallocate them guided by the target view semantic map, especially when there is little overlap or drastic view difference between the source and target images.

Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action Recognition

1 code implementation7 Jul 2022 Zhan Chen, Hong Liu, Tianyu Guo, Zhengyan Chen, Pinhao Song, Hao Tang

First, SkeleMix utilizes the topological information of skeleton data to mix two skeleton sequences by randomly combing the cropped skeleton fragments (the trimmed view) with the remaining skeleton sequences (the truncated view).

Action Recognition Contrastive Learning +2

Interaction Transformer for Human Reaction Generation

1 code implementation4 Jul 2022 Baptiste Chopin, Hao Tang, Naima Otberdout, Mohamed Daoudi, Nicu Sebe

To address this limitation, we propose a novel interaction Transformer (InterFormer) consisting of a Transformer network with both temporal and spatial attention.

Unsupervised High-Resolution Portrait Gaze Correction and Animation

1 code implementation1 Jul 2022 Jichao Zhang, Jingjing Chen, Hao Tang, Enver Sangineto, Peng Wu, Yan Yan, Nicu Sebe, Wei Wang

Solving this problem using an unsupervised method remains an open problem, especially for high-resolution face images in the wild, which are not easy to annotate with gaze and head pose labels.

Image Inpainting

3D-Aware Video Generation

1 code implementation29 Jun 2022 Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou, Hao Tang, Gordon Wetzstein, Leonidas Guibas, Luc van Gool, Radu Timofte

Generative models have emerged as an essential building block for many image synthesis and editing tasks.

Image Generation Video Generation

GraphMLP: A Graph MLP-Like Architecture for 3D Human Pose Estimation

no code implementations13 Jun 2022 Wenhao Li, Hong Liu, Tianyu Guo, Hao Tang, Runwei Ding

To the best of our knowledge, this is the first MLP-Like architecture for 3D human pose estimation in a single frame and a video sequence.

3D Human Pose Estimation Representation Learning

From Perception to Programs: Regularize, Overparameterize, and Amortize

no code implementations13 Jun 2022 Hao Tang, Kevin Ellis

Toward combining inductive reasoning with perception abilities, we develop techniques for neurosymbolic program synthesis where perceptual input is first parsed by neural nets into a low-dimensional interpretable representation, which is then processed by a synthesized program.

Program Synthesis

Medical Image Registration via Neural Fields

no code implementations7 Jun 2022 Shanlin Sun, Kun Han, Hao Tang, Deying Kong, Junayed Naushad, Xiangyi Yan, Xiaohui Xie

Traditional methods for image registration are primarily optimization-driven, finding the optimal deformations that maximize the similarity between two images.

Image Registration Medical Image Registration +1

Real-Time Portrait Stylization on the Edge

no code implementations2 Jun 2022 Yanyu Li, Xuan Shen, Geng Yuan, Jiexiong Guan, Wei Niu, Hao Tang, Bin Ren, Yanzhi Wang

In this work we demonstrate real-time portrait stylization, specifically, translating self-portrait into cartoon or anime style on mobile devices.

DE-Net: Dynamic Text-guided Image Editing Adversarial Networks

1 code implementation2 Jun 2022 Ming Tao, Bing-Kun Bao, Hao Tang, Fei Wu, Longhui Wei, Qi Tian

To solve these limitations, we propose: (i) a Dynamic Editing Block (DEBlock) which composes different editing modules dynamically for various editing requirements.

text-guided-image-editing

AO2-DETR: Arbitrary-Oriented Object Detection Transformer

no code implementations25 May 2022 Linhui Dai, Hong Liu, Hao Tang, Zhiwei Wu, Pinhao Song

Comprehensive experiments on several challenging datasets show that our method achieves superior performance on the AOOD task.

Inductive Bias object-detection +2

Supervised Attention in Sequence-to-Sequence Models for Speech Recognition

no code implementations25 Apr 2022 Gene-Ping Yang, Hao Tang

Attention mechanism in sequence-to-sequence models is designed to model the alignments between acoustic features and output tokens in speech recognition.

speech-recognition Speech Recognition

Deep Algebraic Fitting for Multiple Circle Primitives Extraction from Raw Point Clouds

no code implementations2 Apr 2022 Zeyong Wei, Honghua Chen, Hao Tang, Qian Xie, Mingqiang Wei, Jun Wang

The shape of circle is one of fundamental geometric primitives of man-made engineering objects.

Autoregressive Co-Training for Learning Discrete Speech Representations

1 code implementation29 Mar 2022 Sung-Lin Yeh, Hao Tang

While several self-supervised approaches for learning discrete speech representation have been proposed, it is unclear how these seemingly similar approaches relate to each other.

Quantization

Practical Blind Denoising via Swin-Conv-UNet and Data Synthesis

1 code implementation24 Mar 2022 Kai Zhang, Yawei Li, Jingyun Liang, JieZhang Cao, Yulun Zhang, Hao Tang, Radu Timofte, Luc van Gool

While recent years have witnessed a dramatic upsurge of exploiting deep neural networks toward solving image denoising, existing methods mostly rely on simple noise assumptions, such as additive white Gaussian noise (AWGN), JPEG compression noise and camera sensor noise, and a general-purpose blind denoising method for real images remains unsolved.

Image Denoising Image-to-Image Translation

Cross-View Panorama Image Synthesis

1 code implementation22 Mar 2022 Songsong Wu, Hao Tang, Xiao-Yuan Jing, Haifeng Zhao, Jianjun Qian, Nicu Sebe, Yan Yan

In this paper, we tackle the problem of synthesizing a ground-view panorama image conditioned on a top-view aerial image, which is a challenging problem due to the large gap between the two image domains with different view-points.

Image Generation

Topology-Preserving Shape Reconstruction and Registration via Neural Diffeomorphic Flow

1 code implementation CVPR 2022 Shanlin Sun, Kun Han, Deying Kong, Hao Tang, Xiangyi Yan, Xiaohui Xie

Recently DIFs-based methods have been proposed to handle shape reconstruction and dense point correspondences simultaneously, capturing semantic relationships across shapes of the same class by learning a DIFs-modeled shape template.

Template Matching

Hierarchical Sketch Induction for Paraphrase Generation

1 code implementation ACL 2022 Tom Hosking, Hao Tang, Mirella Lapata

We propose a generative model of paraphrase generation, that encourages syntactic diversity by conditioning on an explicit syntactic sketch.

Paraphrase Generation

Quantum Deep Learning for Mutant COVID-19 Strain Prediction

no code implementations4 Mar 2022 Yu-Xin Jin, Jun-Jie Hu, Qi Li, Zhi-Cheng Luo, Fang-Yan Zhang, Hao Tang, Kun Qian, Xian-Min Jin

New COVID-19 epidemic strains like Delta and Omicron with increased transmissibility and pathogenicity emerge and spread across the whole world rapidly while causing high mortality during the pandemic period.

Local and Global GANs with Semantic-Aware Upsampling for Image Generation

1 code implementation28 Feb 2022 Hao Tang, Ling Shao, Philip H. S. Torr, Nicu Sebe

To learn more discriminative class-specific feature representations for the local generation, we also propose a novel classification module.

Image Generation

Diffeomorphic Image Registration with Neural Velocity Field

no code implementations25 Feb 2022 Kun Han, Shanlin Sun, Xiangyi Yan, Chenyu You, Hao Tang, Junayed Naushad, Haoyu Ma, Deying Kong, Xiaohui Xie

Here we propose a new optimization-based method named DNVF (Diffeomorphic Image Registration with Neural Velocity Field) which utilizes deep neural network to model the space of admissible transformations.

Image Registration

Disentangle Saliency Detection into Cascaded Detail Modeling and Body Filling

no code implementations8 Feb 2022 Yue Song, Hao Tang, Nicu Sebe, Wei Wang

Specifically, the detail modeling focuses on capturing the object edges by supervision of explicitly decomposed detail label that consists of the pixels that are nested on the edge and near the edge.

object-detection Object Detection +2

Continual Attentive Fusion for Incremental Learning in Semantic Segmentation

1 code implementation1 Feb 2022 Guanglei Yang, Enrico Fini, Dan Xu, Paolo Rota, Mingli Ding, Hao Tang, Xavier Alameda-Pineda, Elisa Ricci

To fill this gap, in this paper we introduce a novel attentive feature distillation approach to mitigate catastrophic forgetting while accounting for semantic spatial- and channel-level dependencies.

Incremental Learning Semantic Segmentation

Learning To Restore 3D Face From In-the-Wild Degraded Images

no code implementations CVPR 2022 Zhenyu Zhang, Yanhao Ge, Ying Tai, Xiaoming Huang, Chengjie Wang, Hao Tang, Dongjin Huang, Zhifeng Xie

In-the-wild 3D face modelling is a challenging problem as the predicted facial geometry and texture suffer from a lack of reliable clues or priors, when the input images are degraded.

3D Face Modelling Face Reconstruction

SPViT: Enabling Faster Vision Transformers via Soft Token Pruning

1 code implementation27 Dec 2021 Zhenglun Kong, Peiyan Dong, Xiaolong Ma, Xin Meng, Mengshu Sun, Wei Niu, Xuan Shen, Geng Yuan, Bin Ren, Minghai Qin, Hao Tang, Yanzhi Wang

Moreover, our framework can guarantee the identified model to meet resource specifications of mobile devices and FPGA, and even achieve the real-time execution of DeiT-T on mobile platforms.

Image Classification Model Compression

Geometry-Contrastive Transformer for Generalized 3D Pose Transfer

1 code implementation14 Dec 2021 Haoyu Chen, Hao Tang, Zitong Yu, Nicu Sebe, Guoying Zhao

Specifically, we propose a novel geometry-contrastive Transformer that has an efficient 3D structured perceiving ability to the global geometric inconsistencies across the given meshes.

Pose Transfer

Multi-Modal Perception Attention Network with Self-Supervised Learning for Audio-Visual Speaker Tracking

1 code implementation14 Dec 2021 Yidi Li, Hong Liu, Hao Tang

Multi-modal fusion is proven to be an effective method to improve the accuracy and robustness of speaker tracking, especially in complex scenarios.

Self-Supervised Learning

Graph-based Generative Face Anonymisation with Pose Preservation

1 code implementation10 Dec 2021 Nicola Dall'Asen, Yiming Wang, Hao Tang, Luca Zanella, Elisa Ricci

With the goal to maintain the geometric attributes of the source face, i. e., the facial pose and expression, and to promote more natural face generation, we propose to exploit a Bipartite Graph to explicitly model the relations between the facial landmarks of the source identity and the ones of the condition identity through a deep model.

Face Detection Face Generation

3D-Aware Semantic-Guided Generative Model for Human Synthesis

1 code implementation2 Dec 2021 Jichao Zhang, Enver Sangineto, Hao Tang, Aliaksandr Siarohin, Zhun Zhong, Nicu Sebe, Wei Wang

However, they usually struggle to generate high-quality images representing non-rigid objects, such as the human body, which is of a great interest for many computer graphics applications.

3D-Aware Image Synthesis

Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Model

1 code implementation CVPR 2022 Zipeng Xu, Tianwei Lin, Hao Tang, Fu Li, Dongliang He, Nicu Sebe, Radu Timofte, Luc van Gool, Errui Ding

We propose a novel framework, i. e., Predict, Prevent, and Evaluate (PPE), for disentangled text-driven image manipulation that requires little manual annotation while being applicable to a wide variety of manipulations.

Image Manipulation Language Modelling

Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation

1 code implementation19 Nov 2021 Guanglei Yang, Zhun Zhong, Hao Tang, Mingli Ding, Nicu Sebe, Elisa Ricci

Specifically, in the image translation stage, Bi-Mix leverages the knowledge of day-night image pairs to improve the quality of nighttime image relighting.

Autonomous Driving Image Relighting +2

Highly Efficient Natural Image Matting

no code implementations25 Oct 2021 Yijie Zhong, Bo Li, Lv Tang, Hao Tang, Shouhong Ding

With a lightweight basic convolution block, we build a two-stages framework: Segmentation Network (SN) is designed to capture sufficient semantics and classify the pixels into unknown, foreground and background regions; Matting Refine Network (MRN) aims at capturing detailed texture information and regressing accurate alpha values.

Image Matting

AniFormer: Data-driven 3D Animation with Transformer

1 code implementation20 Oct 2021 Haoyu Chen, Hao Tang, Nicu Sebe, Guoying Zhao

Instead, we introduce AniFormer, a novel Transformer-based architecture, that generates animated 3D sequences by directly taking the raw driving sequences and arbitrary same-type target meshes as inputs.

regression

AFTer-UNet: Axial Fusion Transformer UNet for Medical Image Segmentation

no code implementations20 Oct 2021 Xiangyi Yan, Hao Tang, Shanlin Sun, Haoyu Ma, Deying Kong, Xiaohui Xie

One has to either downsample the image or use cropped local patches to reduce GPU memory usage, which limits its performance.

Image Segmentation Medical Image Segmentation +1

Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation

1 code implementation19 Oct 2021 Bin Ren, Hao Tang, Nicu Sebe

To ease this problem, we propose a novel two-stage framework with a new Cascaded Cross MLP-Mixer (CrossMLP) sub-network in the first stage and one refined pixel-level loss in the second stage.

Translation

TransFusion: Cross-view Fusion with Transformer for 3D Human Pose Estimation

1 code implementation18 Oct 2021 Haoyu Ma, Liangjian Chen, Deying Kong, Zhe Wang, Xingwei Liu, Hao Tang, Xiangyi Yan, Yusheng Xie, Shih-Yao Lin, Xiaohui Xie

The 3D position encoding guided by the epipolar field provides an efficient way of encoding correspondences between pixels of different views.

Ranked #14 on 3D Human Pose Estimation on Human3.6M (using extra training data)

3D Human Pose Estimation 3D Pose Estimation

HFSP: A Hardware-friendly Soft Pruning Framework for Vision Transformers

no code implementations29 Sep 2021 Zhenglun Kong, Peiyan Dong, Xiaolong Ma, Xin Meng, Mengshu Sun, Wei Niu, Bin Ren, Minghai Qin, Hao Tang, Yanzhi Wang

Recently, Vision Transformer (ViT) has continuously established new milestones in the computer vision field, while the high computation and memory cost makes its propagation in industrial production difficult.

Image Classification Model Compression

Stingy Teacher: Sparse Logits Suffice to Fail Knowledge Distillation

no code implementations29 Sep 2021 Haoyu Ma, Yifan Huang, Tianlong Chen, Hao Tang, Chenyu You, Zhangyang Wang, Xiaohui Xie

However, it is unclear why the distorted distribution of the logits is catastrophic to the student model.

Knowledge Distillation

Equivariant Neural Network for Factor Graphs

no code implementations29 Sep 2021 Fan-Yun Sun, Jonathan Kuck, Hao Tang, Stefano Ermon

Several indices used in a factor graph data structure can be permuted without changing the underlying probability distribution.

Inductive Bias

Multi-Sample based Contrastive Loss for Top-k Recommendation

1 code implementation1 Sep 2021 Hao Tang, Guoshuai Zhao, Yuxia Wu, Xueming Qian

Therefore, we propose a Multi-Sample based Contrastive Loss (MSCL) function which solves the two problems by balancing the importance of positive and negative samples and data augmentation.

Contrastive Learning Data Augmentation +1

Layout-to-Image Translation with Double Pooling Generative Adversarial Networks

1 code implementation29 Aug 2021 Hao Tang, Nicu Sebe

In this paper, we address the task of layout-to-image translation, which aims to translate an input semantic layout to a realistic image.

Translation

Recurrent Mask Refinement for Few-Shot Medical Image Segmentation

1 code implementation ICCV 2021 Hao Tang, Xingwei Liu, Shanlin Sun, Xiangyi Yan, Xiaohui Xie

Although having achieved great success in medical image segmentation, deep convolutional neural networks usually require a large dataset with manual annotations for training and are difficult to generalize to unseen classes.

Few-Shot Learning Image Segmentation +2

Cross-View Exocentric to Egocentric Video Synthesis

no code implementations7 Jul 2021 Gaowen Liu, Hao Tang, Hugo Latapie, Jason Corso, Yan Yan

Particularly, we propose a novel Bi-directional Spatial Temporal Attention Fusion Generative Adversarial Network (STA-GAN) to learn both spatial and temporal information to generate egocentric video sequences from the exocentric view.

Video Generation

Total Generate: Cycle in Cycle Generative Adversarial Networks for Generating Human Faces, Hands, Bodies, and Natural Scenes

1 code implementation21 Jun 2021 Hao Tang, Nicu Sebe

Both generators are mutually connected and trained in an end-to-end fashion and explicitly form three cycled subnets, i. e., one image generation cycle and two guidance generation cycles.

Image-to-Image Translation Translation

Controllable Person Image Synthesis with Spatially-Adaptive Warped Normalization

1 code implementation31 May 2021 Jichao Zhang, Aliaksandr Siarohin, Hao Tang, Enver Sangineto, Wei Wang, Humphrey Sh, Nicu Sebe

Moreover, we propose a novel Self-Training Part Replacement (STPR) strategy to refine the model for the texture-transfer task, which improves the quality of the generated clothes and the preservation ability of non-target regions.

Image-to-Image Translation Pose Transfer +1

Transformer-Based Source-Free Domain Adaptation

1 code implementation28 May 2021 Guanglei Yang, Hao Tang, Zhun Zhong, Mingli Ding, Ling Shao, Nicu Sebe, Elisa Ricci

In this paper, we study the task of source-free domain adaptation (SFDA), where the source data are not available during target adaptation.

Knowledge Distillation Source-Free Domain Adaptation

Cloth Interactive Transformer for Virtual Try-On

1 code implementation12 Apr 2021 Bin Ren, Hao Tang, Fanyang Meng, Runwei Ding, Ling Shao, Philip H. S. Torr, Nicu Sebe

2D image-based virtual try-on has attracted increased attention from the multimedia and computer vision communities.

Virtual Try-on

Transformer-Based Attention Networks for Continuous Pixel-Wise Prediction

1 code implementation ICCV 2021 Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe, Elisa Ricci

While convolutional neural networks have shown a tremendous impact on various computer vision tasks, they generally demonstrate limitations in explicitly modeling long-range dependencies due to the intrinsic locality of the convolution operation.

Depth Estimation Depth Prediction +1

Adversarial Shape Learning for Building Extraction in VHR Remote Sensing Images

1 code implementation22 Feb 2021 Lei Ding, Hao Tang, Yahui Liu, Yilei Shi, Xiao Xiang Zhu, Lorenzo Bruzzone

To address this issue, we propose an adversarial shape learning network (ASLNet) to model the building shape patterns that improve the accuracy of building segmentation.

Semantically-Adaptive Upsampling for Layout-to-Image Translation

no code implementations1 Jan 2021 Hao Tang, Nicu Sebe

We propose the Semantically-Adaptive UpSampling (SA-UpSample), a general and highly effective upsampling method for the layout-to-image translation task.

Translation

Spatial Context-Aware Self-Attention Model For Multi-Organ Segmentation

no code implementations16 Dec 2020 Hao Tang, Xingwei Liu, Kun Han, Shanlin Sun, Narisu Bai, Xuming Chen, Huang Qian, Yong liu, Xiaohui Xie

State-of-the-art CNN segmentation models apply either 2D or 3D convolutions on input images, with pros and cons associated with each method: 2D convolution is fast, less memory-intensive but inadequate for extracting 3D contextual information from volumetric images, while the opposite is true for 3D convolution.

Image Segmentation Semantic Segmentation

Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous GNNs

no code implementations NeurIPS 2020 Hao Tang, Zhiao Huang, Jiayuan Gu, Bao-liang Lu, Hao Su

Current graph neural networks (GNNs) lack generalizability with respect to scales (graph sizes, graph diameters, edge weights, etc..) when solving many graph analysis problems.

Towards Scale-Invariant Graph-related Problem Solving by Iterative Homogeneous Graph Neural Networks

1 code implementation26 Oct 2020 Hao Tang, Zhiao Huang, Jiayuan Gu, Bao-liang Lu, Hao Su

Current graph neural networks (GNNs) lack generalizability with respect to scales (graph sizes, graph diameters, edge weights, etc..) when solving many graph analysis problems.

Dual Attention GANs for Semantic Image Synthesis

1 code implementation29 Aug 2020 Hao Tang, Song Bai, Nicu Sebe

We also propose two novel modules, i. e., position-wise Spatial Attention Module (SAM) and scale-wise Channel Attention Module (CAM), to capture semantic structure attention in spatial and channel dimensions, respectively.

Image Generation

Bipartite Graph Reasoning GANs for Person Image Generation

1 code implementation10 Aug 2020 Hao Tang, Song Bai, Philip H. S. Torr, Nicu Sebe

We present a novel Bipartite Graph Reasoning GAN (BiGraphGAN) for the challenging person image generation task.

 Ranked #1 on Pose Transfer on Market-1501 (PCKh metric)

Pose Transfer

Dual In-painting Model for Unsupervised Gaze Correction and Animation in the Wild

1 code implementation9 Aug 2020 Jichao Zhang, Jingjing Chen, Hao Tang, Wei Wang, Yan Yan, Enver Sangineto, Nicu Sebe

In this paper we address the problem of unsupervised gaze correction in the wild, presenting a solution that works without the need for precise annotations of the gaze angle and the head pose.

Quantum Computation for Pricing the Collateralized Debt Obligations

no code implementations6 Aug 2020 Hao Tang, Anurag Pal, Lu-Feng Qiao, Tian-Yu Wang, Jun Gao, Xian-Min Jin

Collateralized debt obligation (CDO) has been one of the most commonly used structured financial products and is intensively studied in quantitative finance.

XingGAN for Person Image Generation

2 code implementations ECCV 2020 Hao Tang, Song Bai, Li Zhang, Philip H. S. Torr, Nicu Sebe

We propose a novel Generative Adversarial Network (XingGAN or CrossingGAN) for person image generation tasks, i. e., translating the pose of a given person to a desired one.

 Ranked #1 on Pose Transfer on Market-1501 (IS metric)

Pose Transfer

AMR Parsing with Latent Structural Information

no code implementations ACL 2020 Qiji Zhou, Yue Zhang, Donghong Ji, Hao Tang

Abstract Meaning Representations (AMRs) capture sentence-level semantics structural representations to broad-coverage natural sentences.

AMR Parsing

Relevant Region Prediction for Crowd Counting

no code implementations20 May 2020 Xinya Chen, Yanrui Bin, Changxin Gao, Nong Sang, Hao Tang

The module builds a fully connected directed graph between the regions of different density where each node (region) is represented by weighted global pooled feature, and GCN is learned to map this region graph to a set of relation-aware regions representations.

Crowd Counting

Vector-Quantized Autoregressive Predictive Coding

2 code implementations17 May 2020 Yu-An Chung, Hao Tang, James Glass

Autoregressive Predictive Coding (APC), as a self-supervised objective, has enjoyed success in learning representations from large amounts of unlabeled data, and the learned representations are rich for many downstream tasks.

Edge Guided GANs with Contrastive Learning for Semantic Image Synthesis

1 code implementation31 Mar 2020 Hao Tang, Xiaojuan Qi, Guolei Sun, Dan Xu, Nicu Sebe, Radu Timofte, Luc van Gool

To tackle 1), we propose to use edge as an intermediate representation which is further adopted to guide image generation via a proposed attention guided edge transfer module.

Contrastive Learning Image Generation

Exocentric to Egocentric Image Generation via Parallel Generative Adversarial Network

no code implementations8 Feb 2020 Gaowen Liu, Hao Tang, Hugo Latapie, Yan Yan

In this paper, we investigate exocentric (third-person) view to egocentric (first-person) view image generation.

Image Generation

Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation

1 code implementation3 Feb 2020 Hao Tang, Philip H. S. Torr, Nicu Sebe

In the first stage, the input image and the conditional semantic guidance are fed into a cycled semantic-guided generation network to produce initial coarse results.

Image-to-Image Translation Translation

Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation

2 code implementations CVPR 2020 Hao Tang, Dan Xu, Yan Yan, Philip H. S. Torr, Nicu Sebe

To tackle this issue, in this work we consider learning the scene generation in a local context, and correspondingly design a local class-specific generative network with semantic maps as a guidance, which separately constructs and learns sub-generators concentrating on the generation of different classes, and is able to provide more scene details.

Image Generation Scene Generation

Asymmetric Generative Adversarial Networks for Image-to-Image Translation

1 code implementation14 Dec 2019 Hao Tang, Dan Xu, Hong Liu, Nicu Sebe

In this paper, we analyze the limitation of the existing symmetric GAN models in asymmetric translation tasks, and propose an AsymmetricGAN model with both translation and reconstruction generators of unequal sizes and different parameter-sharing strategy to adapt to the asymmetric need in both unsupervised and supervised image-to-image translation tasks.

Image-to-Image Translation Translation

Unified Generative Adversarial Networks for Controllable Image-to-Image Translation

1 code implementation12 Dec 2019 Hao Tang, Hong Liu, Nicu Sebe

The proposed model consists of a single generator and a discriminator taking a conditional image and the target controllable structure as input.

Facial Expression Translation Gesture-to-Gesture Translation +2

AttentionGAN: Unpaired Image-to-Image Translation using Attention-Guided Generative Adversarial Networks

2 code implementations27 Nov 2019 Hao Tang, Hong Liu, Dan Xu, Philip H. S. Torr, Nicu Sebe

State-of-the-art methods in image-to-image translation are capable of learning a mapping from a source domain to a target domain with unpaired image data.

Image-to-Image Translation Translation

Improving Semantic Segmentation of Aerial Images Using Patch-based Attention

no code implementations20 Nov 2019 Lei Ding, Hao Tang, Lorenzo Bruzzone

High-level features extracted from the late layers of a neural network are rich in semantic information, yet have blurred spatial details; low-level features extracted from the early layers of a network contain more pixel-level information, but are isolated and noisy.

Semantic Segmentation

Cycle In Cycle Generative Adversarial Networks for Keypoint-Guided Image Generation

1 code implementation2 Aug 2019 Hao Tang, Dan Xu, Gaowen Liu, Wei Wang, Nicu Sebe, Yan Yan

In this work, we propose a novel Cycle In Cycle Generative Adversarial Network (C$^2$GAN) for the task of keypoint-guided image generation.

Image Generation

NoduleNet: Decoupled False Positive Reductionfor Pulmonary Nodule Detection and Segmentation

1 code implementation25 Jul 2019 Hao Tang, Chupeng Zhang, Xiaohui Xie

Pulmonary nodule detection, false positive reduction and segmentation represent three of the most common tasks in the computeraided analysis of chest CT images.

Friction

Cascade Attention Guided Residue Learning GAN for Cross-Modal Translation

1 code implementation3 Jul 2019 Bin Duan, Wei Wang, Hao Tang, Hugo Latapie, Yan Yan

However, in machine learning, this cross-modal learning is a nontrivial task because different modalities have no homogeneous properties.

BIG-bench Machine Learning Translation

Relating Simple Sentence Representations in Deep Neural Networks and the Brain

1 code implementation ACL 2019 Sharmistha Jat, Hao Tang, Partha Talukdar, Tom Mitchell

To the best of our knowledge, this is the first work showing that the MEG brain recording when reading a word in a sentence can be used to distinguish earlier words in the sentence.

GazeCorrection:Self-Guided Eye Manipulation in the wild using Self-Supervised Generative Adversarial Networks

no code implementations arXiv 2019 Jichao Zhang, Meng Sun, Jingjing Chen, Hao Tang, Yan Yan, Xueying Qin, Nicu Sebe

Gaze correction aims to redirect the person's gaze into the camera by manipulating the eye region, and it can be considered as a specific image resynthesis problem.

Resynthesis

Expression Conditional GAN for Facial Expression-to-Expression Translation

no code implementations14 May 2019 Hao Tang, Wei Wang, Songsong Wu, Xinya Chen, Dan Xu, Nicu Sebe, Yan Yan

In this paper, we focus on the facial expression translation task and propose a novel Expression Conditional GAN (ECGAN) which can learn the mapping from one image domain to another one based on an additional expression attribute.

Facial expression generation Facial Expression Translation +1

Time-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification

no code implementations11 May 2019 Achintya kr. Sarkar, Zheng-Hua Tan, Hao Tang, Suwon Shon, James Glass

There are a number of studies about extraction of bottleneck (BN) features from deep neural networks (DNNs)trained to discriminate speakers, pass-phrases and triphone states for improving the performance of text-dependent speaker verification (TD-SV).

Automatic Speech Recognition Contrastive Learning +2

Structured Discriminative Tensor Dictionary Learning for Unsupervised Domain Adaptation

no code implementations11 May 2019 Songsong Wu, Yan Yan, Hao Tang, Jianjun Qian, Jian Zhang, Xiao-Yuan Jing

However, the number of labeled source samples are always limited due to expensive annotation cost in practice, making sub-optimal performance been observed.

Dictionary Learning Pseudo Label +1

Joint Learning of Self-Representation and Indicator for Multi-View Image Clustering

no code implementations11 May 2019 Songsong Wu, Zhiqiang Lu, Hao Tang, Yan Yan, Songhao Zhu, Xiao-Yuan Jing, Zuoyong Li

Multi-view subspace clustering aims to divide a set of multisource data into several groups according to their underlying subspace structure.

Multi-view Subspace Clustering

Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation

3 code implementations CVPR 2019 Hao Tang, Dan Xu, Nicu Sebe, Yanzhi Wang, Jason J. Corso, Yan Yan

In this paper, we propose a novel approach named Multi-Channel Attention SelectionGAN (SelectionGAN) that makes it possible to generate images of natural scenes in arbitrary viewpoints, based on an image of the scene and a novel semantic map.

Bird View Synthesis Cross-View Image-to-Image Translation +1

VoiceID Loss: Speech Enhancement for Speaker Verification

no code implementations7 Apr 2019 Suwon Shon, Hao Tang, James Glass

In this paper, we propose VoiceID loss, a novel loss function for training a speech enhancement model to improve the robustness of speaker verification.

Speaker Verification Speech Enhancement

An Unsupervised Autoregressive Model for Speech Representation Learning

5 code implementations5 Apr 2019 Yu-An Chung, Wei-Ning Hsu, Hao Tang, James Glass

This paper proposes a novel unsupervised autoregressive neural model for learning generic speech representations.

General Classification Representation Learning +1

Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation

8 code implementations28 Mar 2019 Hao Tang, Dan Xu, Nicu Sebe, Yan Yan

To handle the limitation, in this paper we propose a novel Attention-Guided Generative Adversarial Network (AGGAN), which can detect the most discriminative semantic object and minimize changes of unwanted part for semantic manipulation problems without using extra data and models.

Translation Unsupervised Image-To-Image Translation

An End-to-end Framework For Integrated Pulmonary Nodule Detection and False Positive Reduction

no code implementations23 Mar 2019 Hao Tang, Xingwei Liu, Xiaohui Xie

Most of the existing deep learning nodule detection systems are constructed in two steps: a) nodule candidates screening and b) false positive reduction, using two different models trained separately.

Computed Tomography (CT)

Automated pulmonary nodule detection using 3D deep convolutional neural networks

no code implementations23 Mar 2019 Hao Tang, Daniel R. Kim, Xiaohui Xie

Finally, we introduce a method to ensemble models from both stages via consensus to give the final predictions.

Computed Tomography (CT) object-detection +1

Automatic Pulmonary Lobe Segmentation Using Deep Learning

1 code implementation23 Mar 2019 Hao Tang, Chupeng Zhang, Xiaohui Xie

To validate the robustness and performance of our proposed framework trained with a small number of training examples, we further tested our model on CT scans from an independent dataset.

Computed Tomography (CT)

Improving Dense Crowd Counting Convolutional Neural Networks using Inverse k-Nearest Neighbor Maps and Multiscale Upsampling

1 code implementation31 Jan 2019 Greg Olmschenk, Hao Tang, Zhigang Zhu

Gatherings of thousands to millions of people frequently occur for an enormous variety of events, and automated counting of these high-density crowds is useful for safety, management, and measuring significance of an event.

Crowd Counting Management

Attribute-Guided Sketch Generation

1 code implementation28 Jan 2019 Hao Tang, Xinya Chen, Wei Wang, Dan Xu, Jason J. Corso, Nicu Sebe, Yan Yan

To this end, we propose a novel Attribute-Guided Sketch Generative Adversarial Network (ASGAN) which is an end-to-end framework and contains two pairs of generators and discriminators, one of which is used to generate faces with attributes while the other one is employed for image-to-sketch translation.

Translation

Fast and Robust Dynamic Hand Gesture Recognition via Key Frames Extraction and Feature Fusion

1 code implementation15 Jan 2019 Hao Tang, Hong Liu, Wei Xiao, Nicu Sebe

Gesture recognition is a hot topic in computer vision and pattern recognition, which plays a vitally important role in natural human-computer interface.

Hand Gesture Recognition Hand-Gesture Recognition

Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

1 code implementation14 Jan 2019 Hao Tang, Dan Xu, Wei Wang, Yan Yan, Nicu Sebe

State-of-the-art methods for image-to-image translation with Generative Adversarial Networks (GANs) can learn a mapping from one domain to another domain using unpaired image data.

Image-to-Image Translation Translation

Generalizing semi-supervised generative adversarial networks to regression using feature contrasting

no code implementations27 Nov 2018 Greg Olmschenk, Zhigang Zhu, Hao Tang

We first demonstrate the capabilities of semi-supervised regression GANs on a toy dataset which allows for a detailed understanding of how they operate in various circumstances.

Age Estimation Crowd Counting +2

On The Inductive Bias of Words in Acoustics-to-Word Models

no code implementations31 Oct 2018 Hao Tang, James Glass

In addition, we study three types of inductive bias, leveraging a pronunciation dictionary, word boundary annotations, and constraints on word durations.

Inductive Bias

Frame-level speaker embeddings for text-independent speaker recognition and analysis of end-to-end model

1 code implementation12 Sep 2018 Suwon Shon, Hao Tang, James Glass

In this paper, we propose a Convolutional Neural Network (CNN) based speaker recognition model for extracting robust speaker embeddings.

Speaker Recognition Text-Independent Speaker Recognition

Deep Micro-Dictionary Learning and Coding Network

1 code implementation11 Sep 2018 Hao Tang, Heng Wei, Wei Xiao, Wei Wang, Dan Xu, Yan Yan, Nicu Sebe

In this paper, we propose a novel Deep Micro-Dictionary Learning and Coding Network (DDLCN).

Dictionary Learning

Integrated Server for Measurement-Device-Independent Quantum Key Distribution Network

no code implementations26 Aug 2018 Ci-Yu Wang, Jun Gao, Zhi-Qiang Jiao, Lu-Feng Qiao, Ruo-Jing Ren, Zhen Feng, Yuan Chen, Zeng-Quan Yan, Yao Wang, Hao Tang, Xian-Min Jin

Quantum key distribution (QKD), harnessing quantum physics and optoelectronics, may promise unconditionally secure information exchange in theory.

Quantum Physics

GestureGAN for Hand Gesture-to-Gesture Translation in the Wild

1 code implementation14 Aug 2018 Hao Tang, Wei Wang, Dan Xu, Yan Yan, Nicu Sebe

Therefore, this task requires a high-level understanding of the mapping between the input source gesture and the output target gesture.

Data Augmentation Gesture-to-Gesture Translation +1

On Training Recurrent Networks with Truncated Backpropagation Through Time in Speech Recognition

no code implementations9 Jul 2018 Hao Tang, James Glass

In this paper, we study recurrent networks' ability to learn long-term dependency in the context of speech recognition.

speech-recognition Speech Recognition

A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition

no code implementations13 Jun 2018 Hao Tang, Wei-Ning Hsu, Francois Grondin, James Glass

Speech recognizers trained on close-talking speech do not generalize to distant speech and the word error rate degradation can be as large as 40% absolute.

Data Augmentation Distant Speech Recognition +3

Unsupervised Adaptation with Interpretable Disentangled Representations for Distant Conversational Speech Recognition

no code implementations13 Jun 2018 Wei-Ning Hsu, Hao Tang, James Glass

However, it is relatively inexpensive to collect large amounts of unlabeled data from domains that we want the models to generalize to.

Automatic Speech Recognition speech-recognition

Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation

1 code implementation CVPR 2018 Dan Xu, Wei Wang, Hao Tang, Hong Liu, Nicu Sebe, Elisa Ricci

Recent works have shown the benefit of integrating Conditional Random Fields (CRFs) models into deep architectures for improving pixel-level prediction tasks.

Monocular Depth Estimation

Sequence Prediction with Neural Segmental Models

no code implementations5 Sep 2017 Hao Tang

We explore end-to-end training for segmental models with various loss functions, and show how end-to-end training with marginal log loss can eliminate the need for detailed manual alignments.

General Classification

End-to-End Neural Segmental Models for Speech Recognition

no code implementations1 Aug 2017 Hao Tang, Liang Lu, Lingpeng Kong, Kevin Gimpel, Karen Livescu, Chris Dyer, Noah A. Smith, Steve Renals

Segmental models are an alternative to frame-based models for sequence prediction, where hypothesized path weights are based on entire segment scores rather than a single frame at a time.

speech-recognition Speech Recognition

Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition

no code implementations5 Apr 2017 Shubham Toshniwal, Hao Tang, Liang Lu, Karen Livescu

We hypothesize that using intermediate representations as auxiliary supervision at lower levels of deep networks may be a good way of combining the advantages of end-to-end training and more traditional pipeline approaches.

speech-recognition Speech Recognition

End-to-End Training Approaches for Discriminative Segmental Models

no code implementations21 Oct 2016 Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu

Similarly to hybrid HMM-neural network models, segmental models of this class can be trained in two stages (frame classifier training followed by linear segmental model weight training), end to end (joint training of both frame classifier and linear weights), or with end-to-end fine-tuning after two-stage training.

speech-recognition Speech Recognition

Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation

no code implementations26 Sep 2016 Taehwan Kim, Jonathan Keane, Weiran Wang, Hao Tang, Jason Riggle, Gregory Shakhnarovich, Diane Brentari, Karen Livescu

Recognizing fingerspelling is challenging for a number of reasons: It involves quick, small motions that are often highly coarticulated; it exhibits significant variation between signers; and there has been a dearth of continuous fingerspelling data collected.

Efficient Segmental Cascades for Speech Recognition

no code implementations2 Aug 2016 Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu

Discriminative segmental models offer a way to incorporate flexible feature functions into speech recognition.

speech-recognition Speech Recognition

Signer-independent Fingerspelling Recognition with Deep Neural Network Adaptation

no code implementations13 Feb 2016 Taehwan Kim, Weiran Wang, Hao Tang, Karen Livescu

Previous work has shown that it is possible to achieve almost 90% accuracies on fingerspelling recognition in a signer-dependent setting.

Automatic Speech Recognition speech-recognition

Discriminative Segmental Cascades for Feature-Rich Phone Recognition

no code implementations22 Jul 2015 Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu

A typical solution is to use approximate decoding, either by beam pruning in a single pass or by beam pruning to generate a lattice followed by a second pass.

Language Modelling speech-recognition +2

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