1 code implementation • 13 Apr 2022 • Yurui Ren, Xiaoqing Fan, Ge Li, Shan Liu, Thomas H. Li
Our model is trained to predict human images in arbitrary poses, which encourages it to extract disentangled and expressive neural textures representing the appearance of different semantic entities.
no code implementations • 16 Feb 2022 • Pranav Kadam, Qingyang Zhou, Shan Liu, C. -C. Jay Kuo
An unsupervised point cloud object retrieval and pose estimation method, called PCRP, is proposed in this work.
1 code implementation • 12 Feb 2022 • Chunyang Fu, Ge Li, Rui Song, Wei Gao, Shan Liu
In point cloud compression, sufficient contexts are significant for modeling the point cloud distribution.
no code implementations • 8 Dec 2021 • Pranav Kadam, Min Zhang, Shan Liu, C. -C. Jay Kuo
GPCO is an unsupervised learning method that predicts object motion by matching features of consecutive point cloud scans.
no code implementations • 16 Nov 2021 • Wei Jiang, Wei Wang, Songnan Li, Shan Liu
This work addresses two major issues of end-to-end learned image compression (LIC) based on deep neural networks: variable-rate learning where separate networks are required to generate compressed images with varying qualities, and the train-test mismatch between differentiable approximate quantization and true hard quantization.
no code implementations • 24 Sep 2021 • Min Zhang, Pranav Kadam, Shan Liu, C. -C. Jay Kuo
It is named GSIP (Green Segmentation of Indoor Point clouds) and its performance is evaluated on a representative large-scale benchmark -- the Stanford 3D Indoor Segmentation (S3DIS) dataset.
1 code implementation • ICCV 2021 • Yurui Ren, Ge Li, Yuanqi Chen, Thomas H. Li, Shan Liu
The proposed model can generate photo-realistic portrait images with accurate movements according to intuitive modifications.
no code implementations • 4 Aug 2021 • Yurui Ren, Yubo Wu, Thomas H. Li, Shan Liu, Ge Li
Pose-guided person image synthesis aims to synthesize person images by transforming reference images into target poses.
no code implementations • 15 Jun 2021 • Sheng Lin, Wei Jiang, Wei Wang, Kaidi Xu, Yanzhi Wang, Shan Liu, Songnan Li
Compressing Deep Neural Network (DNN) models to alleviate the storage and computation requirements is essential for practical applications, especially for resource limited devices.
no code implementations • 26 May 2021 • Wen Gao, Shan Liu, Xiaozhong Xu, Manouchehr Rafie, Yuan Zhang, Igor Curcio
Specifically, we will first provide an overview of the MPEG VCM group including use cases, requirements, processing pipelines, plan for potential VCM standards, followed by the evaluation framework including machine-vision tasks, dataset, evaluation metrics, and anchor generation.
no code implementations • 16 May 2021 • Xiao Wang, Wei Jiang, Wei Wang, Shan Liu, Brian Kulis, Peter Chin
The key idea is to replace the image to be compressed with a substitutional one that outperforms the original one in a desired way.
no code implementations • 12 May 2021 • Xiaozhong Xu, Shan Liu, Zeqiang Li
Learning-based visual data compression and analysis have attracted great interest from both academia and industry recently.
1 code implementation • 15 Mar 2021 • Pranav Kadam, Min Zhang, Shan Liu, C. -C. Jay Kuo
Inspired by the recent PointHop classification method, an unsupervised 3D point cloud registration method, called R-PointHop, is proposed in this work.
no code implementations • 5 Mar 2021 • Yiming Li, Shan Liu, Yu Chen, Yushan Zheng, Sijia Chen, Bin Zhu, Jian Lou
As the successor of H. 265/HEVC, the new versatile video coding standard (H. 266/VVC) can provide up to 50% bitrate saving with the same subjective quality, at the cost of increased decoding complexity.
no code implementations • ICCV 2021 • Munan Xu, Yuanqi Chen, Shan Liu, Thomas H. Li, Ge Li
Pose-guided virtual try-on task aims to modify the fashion item based on pose transfer task.
no code implementations • ICCV 2021 • Bing Li, Chia-Wen Lin, Cheng Zheng, Shan Liu, Junsong Yuan, Bernard Ghanem, C.-C. Jay Kuo
In the second stage, we derive another warping model to refine warping results in less important regions by eliminating serious distortions in shape, disparity and 3D structure.
1 code implementation • 10 Dec 2020 • Yuanqi Chen, Ge Li, Cece Jin, Shan Liu, Thomas Li
This issue makes the generator lack the incentive from the discriminator to learn high-frequency content of data, resulting in a significant spectrum discrepancy between generated images and real images.
no code implementations • 24 Nov 2020 • Qiao Tian, Yi Chen, Zewang Zhang, Heng Lu, LingHui Chen, Lei Xie, Shan Liu
On one hand, we propose to discriminate ground-truth waveform from synthetic one in frequency domain for offering more consistency guarantees instead of only in time domain.
no code implementations • 2 Sep 2020 • Min Zhang, Pranav Kadam, Shan Liu, C. -C. Jay Kuo
The UFF method exploits statistical correlations of points in a point cloud set to learn shape and point features in a one-pass feedforward manner through a cascaded encoder-decoder architecture.
no code implementations • 2 Sep 2020 • Pranav Kadam, Min Zhang, Shan Liu, C. -C. Jay Kuo
An unsupervised point cloud registration method, called salient points analysis (SPA), is proposed in this work.
1 code implementation • 27 Aug 2020 • Yurui Ren, Ge Li, Shan Liu, Thomas H. Li
We show that our framework can spatially transform the inputs in an efficient manner.
1 code implementation • 28 Jul 2020 • Yuanqi Chen, Xiaoming Yu, Shan Liu, Ge Li
Recent studies have shown remarkable success in unsupervised image-to-image translation.
no code implementations • 7 Jul 2020 • Yanghao Li, Bichuan Guo, Jiangtao Wen, Zhen Xia, Shan Liu, Yuxing Han
Denoisers trained with synthetic data often fail to cope with the diversity of unknown noises, giving way to methods that can adapt to existing noise without knowing its ground truth.
no code implementations • 12 May 2020 • Zewang Zhang, Qiao Tian, Heng Lu, Ling-Hui Chen, Shan Liu
This paper investigates how to leverage a DurIAN-based average model to enable a new speaker to have both accurate pronunciation and fluent cross-lingual speaking with very limited monolingual data.
2 code implementations • 9 Feb 2020 • Min Zhang, Yifan Wang, Pranav Kadam, Shan Liu, C. -C. Jay Kuo
The PointHop method was recently proposed by Zhang et al. for 3D point cloud classification with unsupervised feature extraction.
1 code implementation • 8 Nov 2019 • Wei-Hong Lin, Jia-Xing Zhong, Shan Liu, Thomas Li, Ge Li
Generic object detection algorithms have proven their excellent performance in recent years.
no code implementations • 30 Oct 2019 • Munan Xu, Junming Chen, Haiqiang Wang, Shan Liu, Ge Li, Zhiqiang Bai
However, video quality exhibits different characteristics from static image quality due to the existence of temporal masking effects.
1 code implementation • NeurIPS 2019 • Xiaoming Yu, Yuanqi Chen, Thomas Li, Shan Liu, Ge Li
Recent advances of image-to-image translation focus on learning the one-to-many mapping from two aspects: multi-modal translation and multi-domain translation.
1 code implementation • ICCV 2019 • Yurui Ren, Xiaoming Yu, Ruonan Zhang, Thomas H. Li, Shan Liu, Ge Li
Image inpainting techniques have shown significant improvements by using deep neural networks recently.
3 code implementations • 30 Jul 2019 • Min Zhang, Haoxuan You, Pranav Kadam, Shan Liu, C. -C. Jay Kuo
In the attribute building stage, we address the problem of unordered point cloud data using a space partitioning procedure and developing a robust descriptor that characterizes the relationship between a point and its one-hop neighbor in a PointHop unit.
no code implementations • 29 Jul 2019 • Wei Jia, Li Li, Zhu Li, Xiang Zhang, Shan Liu
The block-based coding structure in the hybrid video coding framework inevitably introduces compression artifacts such as blocking, ringing, etc.
no code implementations • 18 Apr 2019 • Wei Yan, Yiting shao, Shan Liu, Thomas H. Li, Zhu Li, Ge Li
Point cloud is a fundamental 3D representation which is widely used in real world applications such as autonomous driving.
1 code implementation • CVPR 2019 • Jia-Xing Zhong, Nannan Li, Weijie Kong, Shan Liu, Thomas H. Li, Ge Li
Remarkably, we obtain the frame-level AUC score of 82. 12% on UCF-Crime.
no code implementations • 6 Dec 2018 • Qiao Tian, Bing Yang, Jing Chen, Benlai Tang, Shan Liu
Firstly, due to the noisy input signal of the model, there is still a gap between the quality of generated and natural waveforms.
no code implementations • 6 Nov 2018 • Weijie Kong, Nannan Li, Shan Liu, Thomas Li, Ge Li
Despite tremendous progress achieved in temporal action detection, state-of-the-art methods still suffer from the sharp performance deterioration when localizing the starting and ending temporal action boundaries.
no code implementations • 26 Jun 2018 • Xiaoming Yu, Zhenqiang Ying, Thomas Li, Shan Liu, Ge Li
Recent advances in image-to-image translation have seen a rise in approaches generating diverse images through a single network.