Search Results for author: Songyuan Li

Found 14 papers, 4 papers with code

F3A-GAN: Facial Flow for Face Animation with Generative Adversarial Networks

no code implementations12 May 2022 Xintian Wu, Qihang Zhang, Yiming Wu, Huanyu Wang, Songyuan Li, Lingyun Sun, Xi Li

Formulated as a conditional generation problem, face animation aims at synthesizing continuous face images from a single source image driven by a set of conditional face motion.

Multitask Identity-Aware Image Steganography via Minimax Optimization

no code implementations13 Jul 2021 Jiabao Cui, Pengyi Zhang, Songyuan Li, Liangli Zheng, Cuizhu Bao, Jupeng Xia, Xi Li

The key issue of the direct recognition is to preserve identity information of secret images into container images and make container images look similar to cover images at the same time.

Image Restoration Image Steganography

Recent Advances and Trends in Multimodal Deep Learning: A Review

no code implementations24 May 2021 Jabeen Summaira, Xi Li, Amin Muhammad Shoib, Songyuan Li, Jabbar Abdul

Deep Learning has implemented a wide range of applications and has become increasingly popular in recent years.

Multimodal Deep Learning

Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion

1 code implementation CVPR 2021 Peng Sun, Wenhu Zhang, Huanyu Wang, Songyuan Li, Xi Li

In principle, the feature modeling scheme is carried out in a depth-sensitive attention module, which leads to the RGB feature enhancement as well as the background distraction reduction by capturing the depth geometry prior.

object-detection RGB-D Salient Object Detection +2

Unsupervised Domain Adaptation for Image Classification via Structure-Conditioned Adversarial Learning

no code implementations4 Mar 2021 Hui Wang, Jian Tian, Songyuan Li, Hanbin Zhao, Qi Tian, Fei Wu, Xi Li

Unsupervised domain adaptation (UDA) typically carries out knowledge transfer from a label-rich source domain to an unlabeled target domain by adversarial learning.

General Classification Image Classification +2

VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated Scenarios

no code implementations5 Jan 2021 Huanzhang Dou, Wenhu Zhang, Pengyi Zhang, Yuhan Zhao, Songyuan Li, Zequn Qin, Fei Wu, Lin Dong, Xi Li

With the motivation of practical gait recognition applications, we propose to automatically create a large-scale synthetic gait dataset (called VersatileGait) by a game engine, which consists of around one million silhouette sequences of 11, 000 subjects with fine-grained attributes in various complicated scenarios.

Gait Recognition

RDI-Net: Relational Dynamic Inference Networks

1 code implementation ICCV 2021 Huanyu Wang, Songyuan Li, Shihao Su, Zequn Qin, Xi Li

In this paper, we model the relations for dynamic inference from two aspects: the routers and the samples.

ResKD: Residual-Guided Knowledge Distillation

no code implementations8 Jun 2020 Xuewei Li, Songyuan Li, Bourahla Omar, Fei Wu, Xi Li

In this paper, we see knowledge distillation in a fresh light, using the knowledge gap, or the residual, between a teacher and a student as guidance to train a much more lightweight student, called a res-student.

Knowledge Distillation

CoDiNet: Path Distribution Modeling with Consistency and Diversity for Dynamic Routing

1 code implementation29 May 2020 Huanyu Wang, Zequn Qin, Songyuan Li, Xi Li

In this paper, we see dynamic routing networks in a fresh light, formulating a routing method as a mapping from a sample space to a routing space.

Model Compression

Real-Time Semantic Segmentation via Auto Depth, Downsampling Joint Decision and Feature Aggregation

no code implementations31 Mar 2020 Peng Sun, Jiaxiang Wu, Songyuan Li, Peiwen Lin, Junzhou Huang, Xi Li

To satisfy the stringent requirements on computational resources in the field of real-time semantic segmentation, most approaches focus on the hand-crafted design of light-weight segmentation networks.

Neural Architecture Search Real-Time Semantic Segmentation

Cannot find the paper you are looking for? You can Submit a new open access paper.