2 code implementations • 11 Mar 2024 • Xuan Ju, Xian Liu, Xintao Wang, Yuxuan Bian, Ying Shan, Qiang Xu
Image inpainting, the process of restoring corrupted images, has seen significant advancements with the advent of diffusion models (DMs).
no code implementations • 10 Mar 2024 • Youyuan Zhang, Xuan Ju, James J. Clark
By leveraging the self-consistency property of CMs, we eliminate the need for time-consuming inversion or additional condition extraction, reducing editing time.
no code implementations • 22 Feb 2024 • Jingyao Li, Pengguang Chen, Xuan Ju, Hong Xu, Jiaya Jia
Our research aims to bridge the domain gap between natural and artificial scenarios with efficient tuning strategies.
no code implementations • 7 Feb 2024 • Yuxuan Bian, Xuan Ju, Jiangtong Li, Zhijian Xu, Dawei Cheng, Qiang Xu
In this study, we present aLLM4TS, an innovative framework that adapts Large Language Models (LLMs) for time-series representation learning.
1 code implementation • 2 Oct 2023 • Xuan Ju, Ailing Zeng, Yuxuan Bian, Shaoteng Liu, Qiang Xu
Specifically, in the context of diffusion-based editing, where a source image is edited according to a target prompt, the process commences by acquiring a noisy latent vector corresponding to the source image via the diffusion model.
Ranked #3 on Text-based Image Editing on PIE-Bench
1 code implementation • ICCV 2023 • Xuan Ju, Ailing Zeng, Chenchen Zhao, Jianan Wang, Lei Zhang, Qiang Xu
While such a plug-and-play approach is appealing, the inevitable and uncertain conflicts between the original images produced from the frozen SD branch and the given condition incur significant challenges for the learnable branch, which essentially conducts image feature editing for condition enforcement.
1 code implementation • CVPR 2023 • Xuan Ju, Ailing Zeng, Jianan Wang, Qiang Xu, Lei Zhang
Humans have long been recorded in a variety of forms since antiquity.
1 code implementation • 16 Mar 2022 • Ailing Zeng, Xuan Ju, Lei Yang, Ruiyuan Gao, Xizhou Zhu, Bo Dai, Qiang Xu
This paper proposes a simple baseline framework for video-based 2D/3D human pose estimation that can achieve 10 times efficiency improvement over existing works without any performance degradation, named DeciWatch.
Ranked #1 on 2D Human Pose Estimation on JHMDB (2D poses only)
2 code implementations • 27 Dec 2021 • Ailing Zeng, Lei Yang, Xuan Ju, Jiefeng Li, Jianyi Wang, Qiang Xu
With a simple yet effective motion-aware fully-connected network, SmoothNet improves the temporal smoothness of existing pose estimators significantly and enhances the estimation accuracy of those challenging frames as a side-effect.