1 code implementation • 1 Apr 2024 • Jiazheng Xing, Chao Xu, Yijie Qian, Yang Liu, Guang Dai, Baigui Sun, Yong liu, Jingdong Wang
However, the clothing identity uncontrollability and training inefficiency of existing diffusion-based methods, which struggle to maintain the identity even with full parameter training, are significant limitations that hinder the widespread applications.
1 code implementation • 24 Mar 2024 • Xiaojun Hou, Jiazheng Xing, Yijie Qian, Yaowei Guo, Shuo Xin, JunHao Chen, Kai Tang, Mengmeng Wang, Zhengkai Jiang, Liang Liu, Yong liu
Multimodal Visual Object Tracking (VOT) has recently gained significant attention due to its robustness.
Ranked #17 on Rgb-T Tracking on RGBT234
1 code implementation • 4 Mar 2024 • Chao Xu, Yang Liu, Jiazheng Xing, Weida Wang, Mingze Sun, Jun Dan, Tianxin Huang, Siyuan Li, Zhi-Qi Cheng, Ying Tai, Baigui Sun
In this paper, we abstract the process of people hearing speech, extracting meaningful cues, and creating various dynamically audio-consistent talking faces, termed Listening and Imagining, into the task of high-fidelity diverse talking faces generation from a single audio.
no code implementations • 22 Jan 2024 • Mengmeng Wang, Jiazheng Xing, Boyuan Jiang, Jun Chen, Jianbiao Mei, Xingxing Zuo, Guang Dai, Jingdong Wang, Yong liu
In this paper, we introduce a novel Multimodal, Multi-task CLIP adapting framework named \name to address these challenges, preserving both high supervised performance and robust transferability.
1 code implementation • ICCV 2023 • Jiazheng Xing, Mengmeng Wang, Yudi Ruan, Bofan Chen, Yaowei Guo, Boyu Mu, Guang Dai, Jingdong Wang, Yong liu
Class prototype construction and matching are core aspects of few-shot action recognition.
no code implementations • 3 Aug 2023 • Jiazheng Xing, Mengmeng Wang, Xiaojun Hou, Guang Dai, Jingdong Wang, Yong liu
The adapters we design can combine information from video-text multimodal sources for task-oriented spatiotemporal modeling, which is fast, efficient, and has low training costs.
no code implementations • 19 Jan 2023 • Jiazheng Xing, Mengmeng Wang, Yong liu, Boyu Mu
In this paper, we propose SloshNet, a new framework that revisits the spatial and temporal modeling for few-shot action recognition in a finer manner.
2 code implementations • 17 Sep 2021 • Mengmeng Wang, Jiazheng Xing, Yong liu
Moreover, to handle the deficiency of label texts and make use of tremendous web data, we propose a new paradigm based on this multimodal learning framework for action recognition, which we dub "pre-train, prompt and fine-tune".
Ranked #2 on Action Recognition In Videos on Kinetics-400