no code implementations • ICCV 2023 • Liyuan Ma, Tingwei Gao, Haitian Jiang, Haibin Shen, Kejie Huang
To leverage the advantages of both attention and flow simultaneously, we propose Wavelet-aware Image-based Pose Transfer (WaveIPT) to fuse the attention and flow in the wavelet domain.
no code implementations • 28 Oct 2022 • Zeyu Wang, Haibin Shen, Changyou Men, Quan Sun, Kejie Huang
In this paper, we propose a novel task -- Thermal Infrared Image Inpainting, which aims to reconstruct missing regions of TIR images.
no code implementations • 1 Dec 2021 • Liyuan Ma, Kejie Huang, Dongxu Wei, Zhaoyan Ming, Haibin Shen
Human pose transfer aims at transferring the appearance of the source person to the target pose.
no code implementations • 1 Dec 2021 • Liyuan Ma, Kejie Huang, Dongxu Wei, Haibin Shen
In this paper, we focus on person image generation, namely, generating person image under various conditions, e. g., corrupted texture or different pose.
no code implementations • 9 Jan 2021 • Ruibing Song, Kejie Huang, Zongsheng Wang, Haibin Shen
The separation of the data capture and analysis in modern vision systems has led to a massive amount of data transfer between the end devices and cloud computers, resulting in long latency, slow response, and high power consumption.
1 code implementation • 16 Dec 2020 • Dongxu Wei, Xiaowei Xu, Haibin Shen, Kejie Huang
Although existing GAN-based HVMT methods have achieved great success, they either fail to preserve appearance details due to the loss of spatial consistency between synthesized and exemplary images, or generate incoherent video results due to the lack of temporal consistency among video frames.
no code implementations • 18 Jan 2020 • Lirong Wu, Kejie Huang, Haibin Shen, Lianli Gao
In this paper, we propose a video compression method that extracts and compresses the foreground and background of the video separately.
no code implementations • 18 Jan 2020 • Lirong Wu, Kejie Huang, Haibin Shen
The method of importance map has been widely adopted in DNN-based lossy image compression to achieve bit allocation according to the importance of image contents.
no code implementations • 25 Nov 2019 • Dongxu Wei, Xiaowei Xu, Haibin Shen, Kejie Huang
Therefore, each trained model can only generate videos with a specific scene appearance, new models are required to be trained to generate new appearances.