no code implementations • 5 Feb 2024 • Yuqian Fu, Yu Wang, Yixuan Pan, Lian Huai, Xingyu Qiu, Zeyu Shangguan, Tong Liu, Yanwei Fu, Luc van Gool, Xingqun Jiang
This paper studies the challenging cross-domain few-shot object detection (CD-FSOD), aiming to develop an accurate object detector for novel domains with minimal labeled examples.
1 code implementation • 25 Dec 2023 • Wentao Tian, Zheng Wang, Yuqian Fu, Jingjing Chen, Lechao Cheng
A comprehensive understanding of videos is inseparable from describing the action with its contextual action-object interactions.
no code implementations • 12 Dec 2023 • Jianxiong Gao, Yuqian Fu, Yun Wang, Xuelin Qian, Jianfeng Feng, Yanwei Fu
In this paper, we introduce Recon3DMind, an innovative task aimed at reconstructing 3D visuals from Functional Magnetic Resonance Imaging (fMRI) signals, marking a significant advancement in the fields of cognitive neuroscience and computer vision.
no code implementations • 27 Nov 2023 • Siteng Huang, Biao Gong, Yutong Feng, Xi Chen, Yuqian Fu, Yu Liu, Donglin Wang
Experimental results show that existing subject-driven customization methods fail to learn the representative characteristics of actions and struggle in decoupling actions from context features, including appearance.
no code implementations • 14 Aug 2023 • Yilun Zhang, Yuqian Fu, Xingjun Ma, Lizhe Qi, Jingjing Chen, Zuxuan Wu, Yu-Gang Jiang
We are thus motivated to investigate the importance of spatial relations and propose a more accurate few-shot action recognition method that leverages both spatial and temporal information.
2 code implementations • CVPR 2023 • Yuqian Fu, Yu Xie, Yanwei Fu, Yu-Gang Jiang
Thus, inspired by vanilla adversarial learning, a novel model-agnostic meta Style Adversarial training (StyleAdv) method together with a novel style adversarial attack method is proposed for CD-FSL.
Ranked #1 on Cross-Domain Few-Shot on Plantae
1 code implementation • 11 Oct 2022 • Linhai Zhuo, Yuqian Fu, Jingjing Chen, Yixin Cao, Yu-Gang Jiang
The proposed TGDM framework contains a Mixup-3T network for learning classifiers and a dynamic ratio generation network (DRGN) for learning the optimal mix ratio.
1 code implementation • 11 Oct 2022 • Yuqian Fu, Yu Xie, Yanwei Fu, Jingjing Chen, Yu-Gang Jiang
Concretely, to solve the data imbalance problem between the source data with sufficient examples and the auxiliary target data with limited examples, we build our model under the umbrella of multi-expert learning.
1 code implementation • 15 Mar 2022 • Yuqian Fu, Yu Xie, Yanwei Fu, Jingjing Chen, Yu-Gang Jiang
The key challenge of CD-FSL lies in the huge data shift between source and target domains, which is typically in the form of totally different visual styles.
Ranked #2 on Cross-Domain Few-Shot on CUB
1 code implementation • 26 Jul 2021 • Yuqian Fu, Yanwei Fu, Yu-Gang Jiang
Secondly, a novel disentangle module together with a domain classifier is proposed to extract the disentangled domain-irrelevant and domain-specific features.
no code implementations • 25 Jul 2021 • Yuqian Fu, Yanwei Fu, Yu-Gang Jiang
To achieve this, a novel Mesh-based Video Action Imitation (M-VAI) method is proposed by us.
no code implementations • 27 Jan 2021 • Zhihao Liu, Yuqian Fu
Junctions reflect the important geometrical structure information of the image, and are of primary significance to applications such as image matching and motion analysis.
1 code implementation • 20 Oct 2020 • Yuqian Fu, Li Zhang, Junke Wang, Yanwei Fu, Yu-Gang Jiang
Humans can easily recognize actions with only a few examples given, while the existing video recognition models still heavily rely on the large-scale labeled data inputs.
Ranked #1 on Few Shot Action Recognition on Kinetics-100