Search Results for author: Hao Tang

Found 214 papers, 110 papers with code

StoryImager: A Unified and Efficient Framework for Coherent Story Visualization and Completion

2 code implementations9 Apr 2024 Ming Tao, Bing-Kun Bao, Hao Tang, YaoWei Wang, Changsheng Xu

3) The story visualization and continuation models are trained and inferred independently, which is not user-friendly.

Image Generation Story Visualization

HandDiff: 3D Hand Pose Estimation with Diffusion on Image-Point Cloud

2 code implementations4 Apr 2024 Wencan Cheng, Hao Tang, Luc van Gool, Jong Hwan Ko

Extracting keypoint locations from input hand frames, known as 3D hand pose estimation, is a critical task in various human-computer interaction applications.

3D Hand Pose Estimation

Towards Robust 3D Pose Transfer with Adversarial Learning

no code implementations2 Apr 2024 Haoyu Chen, Hao Tang, Ehsan Adeli, Guoying Zhao

This work is driven by the intuition that the robustness of the model can be enhanced by introducing adversarial samples into the training, leading to a more invulnerable model to the noisy inputs, which even can be further extended to directly handling the real-world data like raw point clouds/scans without intermediate processing.

3D Generation Pose Transfer

On the Faithfulness of Vision Transformer Explanations

no code implementations1 Apr 2024 Junyi Wu, Weitai Kang, Hao Tang, Yuan Hong, Yan Yan

In contrast, our proposed SaCo offers a reliable faithfulness measurement, establishing a robust metric for interpretations.

Versatile Navigation under Partial Observability via Value-guided Diffusion Policy

no code implementations1 Apr 2024 Gengyu Zhang, Hao Tang, Yan Yan

To address these deficiencies, we propose a versatile diffusion-based approach for both 2D and 3D route planning under partial observability.

Autonomous Driving Semantic Segmentation

Learning with Unreliability: Fast Few-shot Voxel Radiance Fields with Relative Geometric Consistency

no code implementations26 Mar 2024 YingJie Xu, Bangzhen Liu, Hao Tang, Bailin Deng, Shengfeng He

We propose a voxel-based optimization framework, ReVoRF, for few-shot radiance fields that strategically address the unreliability in pseudo novel view synthesis.

Novel View Synthesis

Towards Online Real-Time Memory-based Video Inpainting Transformers

no code implementations24 Mar 2024 Guillaume Thiry, Hao Tang, Radu Timofte, Luc van Gool

Video inpainting tasks have seen significant improvements in recent years with the rise of deep neural networks and, in particular, vision transformers.

Video Inpainting

Token Transformation Matters: Towards Faithful Post-hoc Explanation for Vision Transformer

no code implementations21 Mar 2024 Junyi Wu, Bin Duan, Weitai Kang, Hao Tang, Yan Yan

To incorporate the influence of token transformation into interpretation, we propose TokenTM, a novel post-hoc explanation method that utilizes our introduced measurement of token transformation effects.

MaskSAM: Towards Auto-prompt SAM with Mask Classification for Medical Image Segmentation

no code implementations21 Mar 2024 Bin Xie, Hao Tang, Bin Duan, Dawen Cai, Yan Yan

Each pair of auxiliary mask and box prompts, which can solve the requirements of extra prompts, is associated with class label predictions by the sum of the auxiliary classifier token and the learnable global classifier tokens in the mask decoder of SAM to solve the predictions of semantic labels.

Image Segmentation Medical Image Segmentation +2

Efficient Pruning of Large Language Model with Adaptive Estimation Fusion

no code implementations16 Mar 2024 Jun Liu, Chao Wu, Changdi Yang, Hao Tang, Haoye Dong, Zhenglun Kong, Geng Yuan, Wei Niu, Dong Huang, Yanzhi Wang

Large language models (LLMs) have become crucial for many generative downstream tasks, leading to an inevitable trend and significant challenge to deploy them efficiently on resource-constrained devices.

Language Modelling Large Language Model

StableGarment: Garment-Centric Generation via Stable Diffusion

no code implementations16 Mar 2024 Rui Wang, Hailong Guo, Jiaming Liu, Huaxia Li, Haibo Zhao, Xu Tang, Yao Hu, Hao Tang, Peipei Li

In this paper, we introduce StableGarment, a unified framework to tackle garment-centric(GC) generation tasks, including GC text-to-image, controllable GC text-to-image, stylized GC text-to-image, and robust virtual try-on.

Denoising Image Generation +1

GiT: Towards Generalist Vision Transformer through Universal Language Interface

2 code implementations14 Mar 2024 Haiyang Wang, Hao Tang, Li Jiang, Shaoshuai Shi, Muhammad Ferjad Naeem, Hongsheng Li, Bernt Schiele, LiWei Wang

Due to its simple design, this paradigm holds promise for narrowing the architectural gap between vision and language.

Language Modelling

Motion Mamba: Efficient and Long Sequence Motion Generation with Hierarchical and Bidirectional Selective SSM

1 code implementation12 Mar 2024 Zeyu Zhang, Akide Liu, Ian Reid, Richard Hartley, Bohan Zhuang, Hao Tang

Human motion generation stands as a significant pursuit in generative computer vision, while achieving long-sequence and efficient motion generation remains challenging.

InstructGIE: Towards Generalizable Image Editing

no code implementations8 Mar 2024 Zichong Meng, Changdi Yang, Jun Liu, Hao Tang, Pu Zhao, Yanzhi Wang

In response to this challenge, our study introduces a novel image editing framework with enhanced generalization robustness by boosting in-context learning capability and unifying language instruction.

Denoising In-Context Learning

Hierarchical Indexing for Retrieval-Augmented Opinion Summarization

1 code implementation1 Mar 2024 Tom Hosking, Hao Tang, Mirella Lapata

We show that HIRO learns an encoding space that is more semantically structured than prior work, and generates summaries that are more representative of the opinions in the input reviews.

Opinion Summarization Retrieval

WorldCoder, a Model-Based LLM Agent: Building World Models by Writing Code and Interacting with the Environment

no code implementations19 Feb 2024 Hao Tang, Darren Key, Kevin Ellis

We give a model-based agent that builds a Python program representing its knowledge of the world based on its interactions with the environment.

Program Synthesis

ICON: Incremental CONfidence for Joint Pose and Radiance Field Optimization

no code implementations17 Jan 2024 Weiyao Wang, Pierre Gleize, Hao Tang, Xingyu Chen, Kevin J Liang, Matt Feiszli

Neural Radiance Fields (NeRF) exhibit remarkable performance for Novel View Synthesis (NVS) given a set of 2D images.

Novel View Synthesis

SSR-Encoder: Encoding Selective Subject Representation for Subject-Driven Generation

1 code implementation26 Dec 2023 Yuxuan Zhang, Yiren Song, Jiaming Liu, Rui Wang, Jinpeng Yu, Hao Tang, Huaxia Li, Xu Tang, Yao Hu, Han Pan, Zhongliang Jing

Recent advancements in subject-driven image generation have led to zero-shot generation, yet precise selection and focus on crucial subject representations remain challenging.

Image Generation

Enlighten-Your-Voice: When Multimodal Meets Zero-shot Low-light Image Enhancement

1 code implementation15 Dec 2023 Xiaofeng Zhang, Zishan Xu, Hao Tang, Chaochen Gu, Wei Chen, Shanying Zhu, Xinping Guan

Low-light image enhancement is a crucial visual task, and many unsupervised methods tend to overlook the degradation of visible information in low-light scenes, which adversely affects the fusion of complementary information and hinders the generation of satisfactory results.

Low-Light Image Enhancement

Efficient-NeRF2NeRF: Streamlining Text-Driven 3D Editing with Multiview Correspondence-Enhanced Diffusion Models

no code implementations13 Dec 2023 Liangchen Song, Liangliang Cao, Jiatao Gu, Yifan Jiang, Junsong Yuan, Hao Tang

In this work, we propose that by incorporating correspondence regularization into diffusion models, the process of 3D editing can be significantly accelerated.

Learning Contrastive Self-Distillation for Ultra-Fine-Grained Visual Categorization Targeting Limited Samples

no code implementations10 Nov 2023 Ziye Fang, Xin Jiang, Hao Tang, Zechao Li

In the field of intelligent multimedia analysis, ultra-fine-grained visual categorization (Ultra-FGVC) plays a vital role in distinguishing intricate subcategories within broader categories.

Contrastive Learning Fine-Grained Visual Categorization

Multi-view Information Integration and Propagation for Occluded Person Re-identification

1 code implementation7 Nov 2023 Neng Dong, Shuanglin Yan, Hao Tang, Jinhui Tang, Liyan Zhang

Moreover, as multiple images with the same identity are not accessible in the testing stage, we devise an Information Propagation (IP) mechanism to distill knowledge from the comprehensive representation to that of a single occluded image.

Person Re-Identification

Towards High-quality HDR Deghosting with Conditional Diffusion Models

no code implementations2 Nov 2023 Qingsen Yan, Tao Hu, Yuan Sun, Hao Tang, Yu Zhu, Wei Dong, Luc van Gool, Yanning Zhang

To address this challenge, we formulate the HDR deghosting problem as an image generation that leverages LDR features as the diffusion model's condition, consisting of the feature condition generator and the noise predictor.

Denoising Image Generation

Towards Matching Phones and Speech Representations

no code implementations26 Oct 2023 Gene-Ping Yang, Hao Tang

We study two key properties that enable matching, namely, whether cluster centroids of self-supervised representations reduce the variability of phone instances and respect the relationship among phones.

Self-Supervised Learning

Pedestrian Accessible Infrastructure Inventory: Assessing Zero-Shot Segmentation on Multi-Mode Geospatial Data for All Pedestrian Types

no code implementations15 Oct 2023 Jiahao Xia, Gavin Gong, Jiawei Liu, Zhigang Zhu, Hao Tang

In this paper, a Segment Anything Model (SAM)-based pedestrian infrastructure segmentation workflow is designed and optimized, which is capable of efficiently processing multi-sourced geospatial data including LiDAR data and satellite imagery data.

Segmentation Zero Shot Segmentation

Does Graph Distillation See Like Vision Dataset Counterpart?

2 code implementations NeurIPS 2023 Beining Yang, Kai Wang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Hao Tang, Yang You, JianXin Li

We validate the proposed SGDD across 9 datasets and achieve state-of-the-art results on all of them: for example, on the YelpChi dataset, our approach maintains 98. 6% test accuracy of training on the original graph dataset with 1, 000 times saving on the scale of the graph.

Anomaly Detection Graph Representation Learning +1

Efficient-3DiM: Learning a Generalizable Single-image Novel-view Synthesizer in One Day

1 code implementation4 Oct 2023 Yifan Jiang, Hao Tang, Jen-Hao Rick Chang, Liangchen Song, Zhangyang Wang, Liangliang Cao

Although the fidelity and generalizability are greatly improved, training such a powerful diffusion model requires a vast volume of training data and model parameters, resulting in a notoriously long time and high computational costs.

Image Generation Novel View Synthesis

Distilling ODE Solvers of Diffusion Models into Smaller Steps

no code implementations28 Sep 2023 Sanghwan Kim, Hao Tang, Fisher Yu

Notably, our method incurs negligible computational overhead compared to previous distillation techniques, facilitating straightforward and rapid integration with existing samplers.

Denoising Knowledge Distillation

Light Field Diffusion for Single-View Novel View Synthesis

no code implementations20 Sep 2023 Yifeng Xiong, Haoyu Ma, Shanlin Sun, Kun Han, Hao Tang, Xiaohui Xie

Starting from the camera pose matrices, LFD transforms them into light field encoding, with the same shape as the reference image, to describe the direction of each ray.

Denoising Novel View Synthesis +1

Delving into Multimodal Prompting for Fine-grained Visual Classification

no code implementations16 Sep 2023 Xin Jiang, Hao Tang, Junyao Gao, Xiaoyu Du, Shengfeng He, Zechao Li

In this paper, we aim to fully exploit the capabilities of cross-modal description to tackle FGVC tasks and propose a novel multimodal prompting solution, denoted as MP-FGVC, based on the contrastive language-image pertaining (CLIP) model.

Classification Fine-Grained Image Classification

Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentation

1 code implementation14 Sep 2023 Zhaochong An, Guolei Sun, Zongwei Wu, Hao Tang, Luc van Gool

Modern approaches have proved the huge potential of addressing semantic segmentation as a mask classification task which is widely used in instance-level segmentation.

Classification Segmentation +2

Adapting Segment Anything Model for Change Detection in HR Remote Sensing Images

1 code implementation4 Sep 2023 Lei Ding, Kun Zhu, Daifeng Peng, Hao Tang, Kuiwu Yang, Lorenzo Bruzzone

In this work, we aim to utilize the strong visual recognition capabilities of VFMs to improve the change detection of high-resolution Remote Sensing Images (RSIs).

Change Detection Interactive Segmentation

M$^3$Net: Multi-view Encoding, Matching, and Fusion for Few-shot Fine-grained Action Recognition

no code implementations6 Aug 2023 Hao Tang, Jun Liu, Shuanglin Yan, Rui Yan, Zechao Li, Jinhui Tang

Due to the scarcity of manually annotated data required for fine-grained video understanding, few-shot fine-grained (FS-FG) action recognition has gained significant attention, with the aim of classifying novel fine-grained action categories with only a few labeled instances.

Decision Making Fine-grained Action Recognition +1

Interactive Neural Painting

no code implementations31 Jul 2023 Elia Peruzzo, Willi Menapace, Vidit Goel, Federica Arrigoni, Hao Tang, Xingqian Xu, Arman Chopikyan, Nikita Orlov, Yuxiao Hu, Humphrey Shi, Nicu Sebe, Elisa Ricci

This paper advances the state of the art in this emerging research domain by proposing the first approach for Interactive NP.

Hybrid-CSR: Coupling Explicit and Implicit Shape Representation for Cortical Surface Reconstruction

no code implementations23 Jul 2023 Shanlin Sun, Thanh-Tung Le, Chenyu You, Hao Tang, Kun Han, Haoyu Ma, Deying Kong, Xiangyi Yan, Xiaohui Xie

We present Hybrid-CSR, a geometric deep-learning model that combines explicit and implicit shape representations for cortical surface reconstruction.

Surface Reconstruction

Edge Guided GANs with Multi-Scale Contrastive Learning for Semantic Image Synthesis

1 code implementation22 Jul 2023 Hao Tang, Guolei Sun, Nicu Sebe, Luc van Gool

To tackle 2), we design an effective module to selectively highlight class-dependent feature maps according to the original semantic layout to preserve the semantic information.

Contrastive Learning Image Generation

Erasing, Transforming, and Noising Defense Network for Occluded Person Re-Identification

1 code implementation14 Jul 2023 Neng Dong, Liyan Zhang, Shuanglin Yan, Hao Tang, Jinhui Tang

Occlusion perturbation presents a significant challenge in person re-identification (re-ID), and existing methods that rely on external visual cues require additional computational resources and only consider the issue of missing information caused by occlusion.

Adversarial Defense Person Re-Identification

Inter-Instance Similarity Modeling for Contrastive Learning

1 code implementation21 Jun 2023 Chengchao Shen, Dawei Liu, Hao Tang, Zhe Qu, Jianxin Wang

In this paper, we propose a novel image mix method, PatchMix, for contrastive learning in Vision Transformer (ViT), to model inter-instance similarities among images.

Contrastive Learning Instance Segmentation +4

Enlighten Anything: When Segment Anything Model Meets Low-Light Image Enhancement

2 code implementations17 Jun 2023 Qihan Zhao, Xiaofeng Zhang, Hao Tang, Chaochen Gu, Shanying Zhu

Image restoration is a low-level visual task, and most CNN methods are designed as black boxes, lacking transparency and intrinsic aesthetics.

Image Restoration Low-Light Image Enhancement +2

Edge-guided Representation Learning for Underwater Object Detection

no code implementations1 Jun 2023 Linhui Dai, Hong Liu, Pinhao Song, Hao Tang, Runwei Ding, Shengquan Li

The key to addressing these challenges is to focus the model on obtaining more discriminative information.

Object object-detection +2

Reversible Graph Neural Network-based Reaction Distribution Learning for Multiple Appropriate Facial Reactions Generation

1 code implementation24 May 2023 Tong Xu, Micol Spitale, Hao Tang, Lu Liu, Hatice Gunes, Siyang Song

This means that we approach this problem by considering the generation of a distribution of the listener's appropriate facial reactions instead of multiple different appropriate facial reactions, i. e., 'many' appropriate facial reaction labels are summarised as 'one' distribution label during training.

Self-supervised Predictive Coding Models Encode Speaker and Phonetic Information in Orthogonal Subspaces

no code implementations21 May 2023 Oli Liu, Hao Tang, Sharon Goldwater

Self-supervised speech representations are known to encode both speaker and phonetic information, but how they are distributed in the high-dimensional space remains largely unexplored.

Disentanglement

Attributable and Scalable Opinion Summarization

1 code implementation19 May 2023 Tom Hosking, Hao Tang, Mirella Lapata

We propose a method for unsupervised opinion summarization that encodes sentences from customer reviews into a hierarchical discrete latent space, then identifies common opinions based on the frequency of their encodings.

Opinion Summarization Unsupervised Opinion Summarization

Master: Meta Style Transformer for Controllable Zero-Shot and Few-Shot Artistic Style Transfer

no code implementations CVPR 2023 Hao Tang, Songhua Liu, Tianwei Lin, Shaoli Huang, Fu Li, Dongliang He, Xinchao Wang

On the other hand, different from the vanilla version, we adopt a learnable scaling operation on content features before content-style feature interaction, which better preserves the original similarity between a pair of content features while ensuring the stylization quality.

Meta-Learning Style Transfer

Localized Region Contrast for Enhancing Self-Supervised Learning in Medical Image Segmentation

no code implementations6 Apr 2023 Xiangyi Yan, Junayed Naushad, Chenyu You, Hao Tang, Shanlin Sun, Kun Han, Haoyu Ma, James Duncan, Xiaohui Xie

In this paper, we propose a novel contrastive learning framework that integrates Localized Region Contrast (LRC) to enhance existing self-supervised pre-training methods for medical image segmentation.

Contrastive Learning Image Segmentation +5

Graph Transformer GANs for Graph-Constrained House Generation

no code implementations CVPR 2023 Hao Tang, Zhenyu Zhang, Humphrey Shi, Bo Li, Ling Shao, Nicu Sebe, Radu Timofte, Luc van Gool

We present a novel graph Transformer generative adversarial network (GTGAN) to learn effective graph node relations in an end-to-end fashion for the challenging graph-constrained house generation task.

Generative Adversarial Network House Generation +1

Analysis and Evaluation of Explainable Artificial Intelligence on Suicide Risk Assessment

no code implementations9 Mar 2023 Hao Tang, Aref Miri Rekavandi, Dharjinder Rooprai, Girish Dwivedi, Frank Sanfilippo, Farid Boussaid, Mohammed Bennamoun

This study investigates the effectiveness of Explainable Artificial Intelligence (XAI) techniques in predicting suicide risks and identifying the dominant causes for such behaviours.

Data Augmentation Decision Making +2

DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network

1 code implementation CVPR 2023 Xuan Shen, Yaohua Wang, Ming Lin, Yilun Huang, Hao Tang, Xiuyu Sun, Yanzhi Wang

To this end, a novel framework termed Mathematical Architecture Design for Deep CNN (DeepMAD) is proposed to design high-performance CNN models in a principled way.

Image Classification Neural Architecture Search

Bipartite Graph Diffusion Model for Human Interaction Generation

1 code implementation24 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.

Pruning Parameterization With Bi-Level Optimization for Efficient Semantic Segmentation on the Edge

no code implementations CVPR 2023 Changdi Yang, Pu Zhao, Yanyu Li, Wei Niu, Jiexiong Guan, Hao Tang, Minghai Qin, Bin Ren, Xue Lin, Yanzhi Wang

With the ever-increasing popularity of edge devices, it is necessary to implement real-time segmentation on the edge for autonomous driving and many other applications.

Autonomous Driving Segmentation +1

Learning Concordant Attention via Target-aware Alignment for Visible-Infrared Person Re-identification

no code implementations ICCV 2023 Jianbing Wu, Hong Liu, Yuxin Su, Wei Shi, Hao Tang

Owing to the large distribution gap between the heterogeneous data in Visible-Infrared Person Re-identification (VI Re-ID), we point out that existing paradigms often suffer from the inter-modal semantic misalignment issue and thus fail to align and compare local details properly.

Cross-Modal Retrieval Person Re-Identification +1

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 +4

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.

Compressing Transformer-based self-supervised models for speech processing

1 code implementation17 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 Model Compression +1

MelHuBERT: A simplified HuBERT on Mel spectrograms

1 code implementation17 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.

Automatic Speech Recognition Self-Supervised Learning +3

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.

Generative Adversarial Network 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

Data Level Lottery Ticket Hypothesis for Vision Transformers

1 code implementation2 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.

Analogical Similarity 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

ADPS: Asymmetric Distillation Post-Segmentation for Image Anomaly Detection

no code implementations19 Oct 2022 Peng Xing, Hao Tang, Jinhui Tang, Zechao Li

However, existing KDAD methods suffer from two main limitations: 1) the student network can effortlessly replicate the teacher network's representations, and 2) the features of the teacher network serve solely as a ``reference standard" and are not fully leveraged.

Anomaly Detection Knowledge Distillation

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, Zhixiang Wang, Hanxun Yu, Zhubo Li, Shin'ichi Satoh, Luc van Gool, Zheng Wang

Building upon this foundation, we uncover the pervasive role of artifacts carrying adversarial perturbations in the physical world.

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

2D Human Pose Estimation 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 Generative Adversarial Network +1

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

Moreover, existing methods seldom consider the information inequality problem between modalities caused by image-specific information.

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

Generative Neural Radiance Fields (GNeRF) based 3D-aware GANs have demonstrated remarkable capabilities in generating high-quality images while maintaining strong 3D consistency.

Attribute Disentanglement +2

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.

Cloth-Changing Person Re-Identification Human Parsing

G2P-DDM: Generating Sign Pose Sequence from Gloss Sequence with Discrete Diffusion Model

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

Our approach focuses on the transformation of sign gloss sequences into their corresponding sign pose sequences (G2P).

Denoising Quantization +1

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.

Generative Adversarial Network Image Segmentation +2

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

RZCR: Zero-shot Character Recognition via Radical-based Reasoning

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

The long-tail effect is a common issue that limits the performance of deep learning models on real-world datasets.

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

1 code implementation9 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.

Generative Adversarial Network

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 Vocal Bursts Intensity Prediction

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

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

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

1 code implementation13 Jun 2022 Wenhao Li, Hong Liu, Tianyu Guo, Runwei Ding, Hao Tang

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

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

1 code implementation25 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 +4

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 Image Denoising via Swin-Conv-UNet and Data Synthesis

2 code implementations24 Mar 2022 Kai Zhang, Yawei Li, Jingyun Liang, JieZhang Cao, Yulun Zhang, Hao Tang, Deng-Ping Fan, 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.

Organ Segmentation 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 Sentence

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.

Feature Upsampling 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.

Efficient ViTs 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 +3

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

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 +3

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

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 #20 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 +4

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.

Generative Adversarial Network 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.

Generative Adversarial Network Image-to-Image Translation +1

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, Philip H. S. Torr, Nicu Sebe

In the second stage, we put forth a CIT reasoning block for establishing global mutual interactive dependencies among person representation, the warped clothing item, and the corresponding warped cloth mask.

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.

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 Organ Segmentation +2

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 Position

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)

Generative Adversarial Network Pose Transfer