no code implementations • 22 Apr 2024 • Zeyu Li, Ruitong Gan, Chuanchen Luo, Yuxi Wang, Jiaheng Liu, Ziwei Zhu Man Zhang, Qing Li, XuCheng Yin, Zhaoxiang Zhang, Junran Peng
Driven by powerful image diffusion models, recent research has achieved the automatic creation of 3D objects from textual or visual guidance.
no code implementations • 23 Mar 2024 • Mengqi Zhou, Jun Hou, Chuanchen Luo, Yuxi Wang, Zhaoxiang Zhang, Junran Peng
Due to its great application potential, large-scale scene generation has drawn extensive attention in academia and industry.
3 code implementations • 18 Mar 2024 • Hongbo Zhao, Bolin Ni, Haochen Wang, Junsong Fan, Fei Zhu, Yuxi Wang, Yuntao Chen, Gaofeng Meng, Zhaoxiang Zhang
(i) For unwanted knowledge, efficient and effective deleting is crucial.
no code implementations • 31 Jan 2024 • Xu Hu, Yuxi Wang, Lue Fan, Junsong Fan, Junran Peng, Zhen Lei, Qing Li, Zhaoxiang Zhang
In this paper, we propose a novel approach to achieve object segmentation in 3D Gaussian via an interactive procedure without any training process and learned parameters.
no code implementations • 7 Jan 2024 • Genghao Zhang, Yuxi Wang, Chuanchen Luo, Shibiao Xu, Zhaoxiang Zhang, Man Zhang, Junran Peng
Indoor scene generation has attracted significant attention recently as it is crucial for applications of gaming, virtual reality, and interior design.
1 code implementation • 21 Dec 2023 • Haochen Wang, Junsong Fan, Yuxi Wang, Kaiyou Song, Tiancai Wang, Xiangyu Zhang, Zhaoxiang Zhang
To empower the model as a teacher, we propose Hard Patches Mining (HPM), predicting patch-wise losses and subsequently determining where to mask.
1 code implementation • 22 Nov 2023 • Yuxi Wang, Haibin Ling, Bingyao Huang
Full projector compensation is a practical task of projector-camera systems.
no code implementations • ICCV 2023 • Yuxi Wang, Jian Liang, Jun Xiao, Shuqi Mei, Yuran Yang, Zhaoxiang Zhang
One-shot domain adaptation methods attempt to overcome these challenges by transferring the pre-trained source model to the target domain using only one target data.
1 code implementation • NeurIPS 2023 • Haochen Wang, Junsong Fan, Yuxi Wang, Kaiyou Song, Tong Wang, Zhaoxiang Zhang
As it is empirically observed that Vision Transformers (ViTs) are quite insensitive to the order of input tokens, the need for an appropriate self-supervised pretext task that enhances the location awareness of ViTs is becoming evident.
no code implementations • 19 Aug 2023 • Geng Liu, Yuxi Wang
Domain generalization (DG) attempts to generalize a model trained on single or multiple source domains to the unseen target domain.
no code implementations • 2 Aug 2023 • Jingfan Chen, Yuxi Wang, Pengfei Wang, Xiao Chen, Zhaoxiang Zhang, Zhen Lei, Qing Li
The Class Incremental Semantic Segmentation (CISS) extends the traditional segmentation task by incrementally learning newly added classes.
no code implementations • 4 Jun 2023 • Haochen Wang, Yuchao Wang, Yujun Shen, Junsong Fan, Yuxi Wang, Zhaoxiang Zhang
A common practice is to select the highly confident predictions as the pseudo-ground-truths for each pixel, but it leads to a problem that most pixels may be left unused due to their unreliability.
no code implementations • 23 May 2023 • Haochen Wang, Yujun Shen, Jingjing Fei, Wei Li, Liwei Wu, Yuxi Wang, Zhaoxiang Zhang
To this end, we propose T2S-DA, which we interpret as a form of pulling Target to Source for Domain Adaptation, encouraging the model in learning similar cross-domain features.
1 code implementation • CVPR 2023 • Haochen Wang, Kaiyou Song, Junsong Fan, Yuxi Wang, Jin Xie, Zhaoxiang Zhang
We observe that the reconstruction loss can naturally be the metric of the difficulty of the pre-training task.
no code implementations • 16 Mar 2023 • Wenjian Wang, Lijuan Duan, Yuxi Wang, Junsong Fan, Zhi Gong, Zhaoxiang Zhang
Research into Cross-Domain Few-Shot (CDFS) has emerged to address this issue, forming a more challenging and realistic setting.
no code implementations • ICCV 2023 • Jingtao Wang, Zengjie Song, Yuxi Wang, Jun Xiao, Yuran Yang, Shuqi Mei, Zhaoxiang Zhang
Surrogate gradient (SG) is one of the most effective approaches for training spiking neural networks (SNNs).
1 code implementation • 16 Aug 2022 • Lorenz Stangier, Ji-Ung Lee, Yuxi Wang, Marvin Müller, Nicholas Frick, Joachim Metternich, Iryna Gurevych
We evaluate TexPrax in a user-study with German factory employees who ask their colleagues for solutions on problems that arise during their daily work.
1 code implementation • CVPR 2022 • Zengjie Song, Yuxi Wang, Junsong Fan, Tieniu Tan, Zhaoxiang Zhang
Sound source localization in visual scenes aims to localize objects emitting the sound in a given image.
no code implementations • CVPR 2022 • Wenjian Wang, Lijuan Duan, Yuxi Wang, Qing En, Junsong Fan, Zhaoxiang Zhang
To remedy this problem, we propose an interesting and challenging cross-domain few-shot semantic segmentation task, where the training and test tasks perform on different domains.
no code implementations • 22 Jun 2021 • Yuxi Wang, Jian Liang, Zhaoxiang Zhang
It is the first work to use negative pseudo labels during self-training for domain adaptation.
no code implementations • ICCV 2021 • Yuxi Wang, Junran Peng, Zhaoxiang Zhang
Unsupervised domain adaptation for semantic segmentation aims to assign the pixel-level labels for unlabeled target domain by transferring knowledge from the labeled source domain.
no code implementations • 15 Jun 2016 • Qiang Guo, Hongwei Chen, Yuxi Wang, Yong Guo, Peng Liu, Xiurui Zhu, Zheng Cheng, Zhenming Yu, Minghua Chen, Sigang Yang, Shizhong Xie
However, according to CS theory, image reconstruction is an iterative process that consumes enormous amounts of computational time and cannot be performed in real time.