no code implementations • 26 Mar 2024 • Qilin Wang, Jiangning Zhang, Chengming Xu, Weijian Cao, Ying Tai, Yue Han, Yanhao Ge, Hong Gu, Chengjie Wang, Yanwei Fu
Facial Appearance Editing (FAE) aims to modify physical attributes, such as pose, expression and lighting, of human facial images while preserving attributes like identity and background, showing great importance in photograph.
1 code implementation • 31 Dec 2023 • Yue Han, Jiangning Zhang, Junwei Zhu, Xiangtai Li, Yanhao Ge, Wei Li, Chengjie Wang, Yong liu, Xiaoming Liu, Ying Tai
This work presents FaceX framework, a novel facial generalist model capable of handling diverse facial tasks simultaneously.
no code implementations • 1 Sep 2023 • Yue Han, Jiangpeng He, Mridul Gupta, Edward J. Delp, Fengqing Zhu
Image-based dietary assessment serves as an efficient and accurate solution for recording and analyzing nutrition intake using eating occasion images as input.
2 code implementations • 27 May 2023 • Xuhai Chen, Yue Han, Jiangning Zhang
In this challenge, our method achieved first place in the zero-shot track, especially excelling in segmentation with an impressive F1 score improvement of 0. 0489 over the second-ranked participant.
no code implementations • ICCV 2023 • Xintian Shen, Jiangning Zhang, Jun Chen, Shipeng Bai, Yue Han, Yabiao Wang, Chengjie Wang, Yong liu
To address this issue, we propose a novel Global-aware Kernel Network (GKNet) to harmonize local regions with comprehensive consideration of long-distance background references.
Ranked #5 on Image Harmonization on iHarmony4
no code implementations • CVPR 2023 • Chao Xu, Junwei Zhu, Jiangning Zhang, Yue Han, Wenqing Chu, Ying Tai, Chengjie Wang, Zhifeng Xie, Yong liu
Specifically, we supplement the emotion style in text prompts and use an Aligned Multi-modal Emotion encoder to embed the text, image, and audio emotion modality into a unified space, which inherits rich semantic prior from CLIP.
no code implementations • 16 Mar 2023 • WenJin Fu, Yue Han, Jiangpeng He, Sriram Baireddy, Mridul Gupta, Fengqing Zhu
Therefore, we aim to explore the capability and improve the performance of GAN methods for food image generation.
1 code implementation • 28 Jan 2023 • Weikang Wang, Guanhua Chen, Hanqing Wang, Yue Han, Yun Chen
In this paper, we investigate whether multilingual sentence Transformer LaBSE is a strong multilingual word aligner.
no code implementations • 19 Jan 2023 • Yue Han, Sri Kalyan Yarlagadda, Tonmoy Ghosh, Fengqing Zhu, Edward Sazonov, Edward J. Delp
In this paper, we propose an approach to pre-process images collected by the AIM imaging sensor by rejecting extremely blurry images to improve the performance of food detection.
1 code implementation • 3 Jan 2023 • Yue Han, Jiangning Zhang, Zhucun Xue, Chao Xu, Xintian Shen, Yabiao Wang, Chengjie Wang, Yong liu, Xiangtai Li
In this work, we explore a simple yet unified solution for FSIS as well as its incremental variants, and introduce a new framework named Reference Twice (RefT) to fully explore the relationship between support/query features based on a Transformer-like framework.
no code implementations • 7 Dec 2022 • Yue Han, Christopher Jerrett, Elliot Anshelevich
In particular, we show that for any such pair of objectives, it is always possible to choose an outcome which simultaneously approximates both objectives within a factor of $1+\sqrt{2}$, and give a precise characterization of how this factor improves as the two objectives being optimized become more similar.
no code implementations • 12 Jan 2022 • Jiangning Zhang, Chao Xu, Jian Li, Yue Han, Yabiao Wang, Ying Tai, Yong liu
In the practical application of restoring low-resolution gray-scale images, we generally need to run three separate processes of image colorization, super-resolution, and dows-sampling operation for the target device.
no code implementations • 5 Oct 2021 • Zeman Shao, Yue Han, Jiangpeng He, Runyu Mao, Janine Wright, Deborah Kerr, Carol Boushey, Fengqing Zhu
Accurate assessment of dietary intake requires improved tools to overcome limitations of current methods including user burden and measurement error.