no code implementations • 11 Mar 2024 • Jiaxin Guo, Jiangliu Wang, Zhaoshuo Li, Tongyu Jia, Qi Dou, Yun-hui Liu
Soft tissue tracking is crucial for computer-assisted interventions.
1 code implementation • 26 Nov 2023 • Chongjian Ge, Xiaohan Ding, Zhan Tong, Li Yuan, Jiangliu Wang, Yibing Song, Ping Luo
The attention map is computed based on the mixtures of tokens and group proxies and used to re-combine the tokens and groups in Value.
no code implementations • 25 Sep 2023 • Jiangliu Wang, Jianbo Jiao, Yibing Song, Stephen James, Zhan Tong, Chongjian Ge, Pieter Abbeel, Yun-hui Liu
This work aims to improve unsupervised audio-visual pre-training.
no code implementations • 30 Mar 2023 • Chongjian Ge, Jiangliu Wang, Zhan Tong, Shoufa Chen, Yibing Song, Ping Luo
We evaluate our soft neighbor contrastive learning method (SNCLR) on standard visual recognition benchmarks, including image classification, object detection, and instance segmentation.
2 code implementations • 26 May 2022 • Shoufa Chen, Chongjian Ge, Zhan Tong, Jiangliu Wang, Yibing Song, Jue Wang, Ping Luo
To address this challenge, we propose an effective adaptation approach for Transformer, namely AdaptFormer, which can adapt the pre-trained ViTs into many different image and video tasks efficiently.
no code implementations • CVPR 2021 • Haoang Li, Kai Chen, Ji Zhao, Jiangliu Wang, Pyojin Kim, Zhe Liu, Yun-hui Liu
In contrast, we propose the first approach suitable for both structured and unstructured scenes.
2 code implementations • 31 Aug 2020 • Jiangliu Wang, Jianbo Jiao, Linchao Bao, Shengfeng He, Wei Liu, Yun-hui Liu
Specifically, given an unlabeled video clip, we compute a series of spatio-temporal statistical summaries, such as the spatial location and dominant direction of the largest motion, the spatial location and dominant color of the largest color diversity along the temporal axis, etc.
1 code implementation • ECCV 2020 • Jiangliu Wang, Jianbo Jiao, Yun-hui Liu
This paper addresses the problem of self-supervised video representation learning from a new perspective -- by video pace prediction.
1 code implementation • CVPR 2019 • Jiangliu Wang, Jianbo Jiao, Linchao Bao, Shengfeng He, Yun-hui Liu, Wei Liu
We conduct extensive experiments with C3D to validate the effectiveness of our proposed approach.
Ranked #47 on Self-Supervised Action Recognition on HMDB51