no code implementations • 24 Mar 2024 • Jie Tian, Lingxiao Yang, Ran Ji, Yuexin Ma, Lan Xu, Jingyi Yu, Ye Shi, Jingya Wang
Here, the object motion diffusion model generates sequences of object motions based on gaze conditions, while the hand motion diffusion model produces hand motions based on the generated object motion.
no code implementations • 5 Feb 2024 • Lingxiao Yang, Shutong Ding, Yifan Cai, Jingyi Yu, Jingya Wang, Ye Shi
We theoretically show the existence of manifold deviation by establishing a certain lower bound for the estimation error of the loss guidance.
no code implementations • 29 Dec 2023 • Yun Chen, Lingxiao Yang, Qi Chen, Jian-Huang Lai, Xiaohua Xie
We introduce a two-stage pipeline to effectively train our network: Stage I utilizes inter-speech contrastive learning to model fine-grained emotion and intra-speech disentanglement learning to better separate emotion and content.
no code implementations • 11 Jul 2023 • Zixuan Chen, Lingxiao Yang, JianHuang Lai, Xiaohua Xie
However, these methods have not considered the correlation between adjacent projection views, resulting in aliasing artifacts on SV sinograms.
no code implementations • 28 Mar 2023 • Zixuan Chen, Xiaohua Xie, Lingxiao Yang, JianHuang Lai
Additionally, to meet the speed-accuracy demands, we further propose \textbf{P}ixel-level \textbf{T}emplate \textbf{S}election (PTS) to streamline the original template set.
Ranked #13 on Anomaly Detection on MVTec LOCO AD
1 code implementation • ICCV 2023 • Zixuan Chen, Jian-Huang Lai, Lingxiao Yang, Xiaohua Xie
Medical image arbitrary-scale super-resolution (MIASSR) has recently gained widespread attention, aiming to super sample medical volumes at arbitrary scales via a single model.
no code implementations • 20 Mar 2023 • Yuxuan Shi, Lingxiao Yang, Wangpeng An, XianTong Zhen, Liuqing Wang
The channel attention mechanism is a useful technique widely employed in deep convolutional neural networks to boost the performance for image processing tasks, eg, image classification and image super-resolution.
1 code implementation • 22 Sep 2022 • Yipeng Gao, Lingxiao Yang, Yunmu Huang, Song Xie, Shiyong Li, Wei-Shi Zheng
Under the domain shift, cross-domain few-shot object detection aims to adapt object detectors in the target domain with a few annotated target data.
1 code implementation • 17 Aug 2022 • Shengyu Zhang, Lingxiao Yang, Dong Yao, Yujie Lu, Fuli Feng, Zhou Zhao, Tat-Seng Chua, Fei Wu
Specifically, Re4 encapsulates three backward flows, i. e., 1) Re-contrast, which drives each interest embedding to be distinct from other interests using contrastive learning; 2) Re-attend, which ensures the interest-item correlation estimation in the forward flow to be consistent with the criterion used in final recommendation; and 3) Re-construct, which ensures that each interest embedding can semantically reflect the information of representative items that relate to the corresponding interest.
2 code implementations • Proceedings of Machine Learning Research 2022 • Lingxiao Yang, Ru-Yuan Zhang, Lida Li, Xiaohua Xie
Another advantage of the module is that most of the operators are selected based on the solution to the defined energy function, avoiding too many efforts for structure tuning.
1 code implementation • CVPR 2023 • Huajun Zhou, Bo Qiao, Lingxiao Yang, JianHuang Lai, Xiaohua Xie
In this paper, we propose a novel USOD method to mine rich and accurate saliency knowledge from both easy and hard samples.
1 code implementation • 19 Jun 2022 • Jianxiong Tang, JianHuang Lai, Xiaohua Xie, Lingxiao Yang, Wei-Shi Zheng
The SNN2ANN consists of 2 components: a) a weight sharing architecture between ANN and SNN and b) spiking mapping units.
1 code implementation • CVPR 2022 • Pengze Zhang, Lingxiao Yang, JianHuang Lai, Xiaohua Xie
Pose Guided Person Image Generation (PGPIG) is the task of transforming a person image from the source pose to a given target pose.
1 code implementation • CVPR 2022 • Qi Chen, Lingxiao Yang, JianHuang Lai, Xiaohua Xie
Weakly Supervised Semantic Segmentation (WSSS) based on image-level labels has attracted much attention due to low annotation costs.
Ranked #20 on Weakly-Supervised Semantic Segmentation on COCO 2014 val
Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation
1 code implementation • 7 Feb 2022 • Huajun Zhou, Yang Lin, Lingxiao Yang, JianHuang Lai, Xiaohua Xie
In recent years, deep network-based methods have continuously refreshed state-of-the-art performance on Salient Object Detection (SOD) task.
1 code implementation • 7 Dec 2021 • Huajun Zhou, Peijia Chen, Lingxiao Yang, JianHuang Lai, Xiaohua Xie
Moreover, a new loss function is proposed to facilitate the generation of high-quality pseudo labels.