no code implementations • 6 Jan 2024 • Tongyan Hua, Haotian Bai, Zidong Cao, Ming Liu, DaCheng Tao, Lin Wang
In this paper, we introduce Hi-Map, a novel monocular dense mapping approach based on Neural Radiance Field (NeRF).
no code implementations • ICCV 2023 • Haotian Bai, Yiqi Lin, Yize Chen, Lin Wang
The explicit neural radiance field (NeRF) has gained considerable interest for its efficient training and fast inference capabilities, making it a promising direction such as virtual reality and gaming.
no code implementations • 1 Jun 2023 • Tongyan Hua, Haotian Bai, Zidong Cao, Lin Wang
We then propose the sliding window sampler to reduce uncertainty by incorporating coherent geometric cues from observed frames during map initialization to enhance convergence.
no code implementations • 24 Mar 2023 • Haotian Bai, Yuanhuiyi Lyu, Lutao Jiang, Sijia Li, Haonan Lu, Xiaodong Lin, Lin Wang
To tackle the issue of 'guidance collapse' and enhance consistency, we propose a novel framework, dubbed CompoNeRF, by integrating an editable 3D scene layout with object specific and scene-wide guidance mechanisms.
1 code implementation • CVPR 2023 • Jinjing Zhu, Haotian Bai, Lin Wang
We solve this problem from a game theory's perspective with the proposed model dubbed as PMTrans, which bridges source and target domains with an intermediate domain.
Ranked #1 on Unsupervised Domain Adaptation on Office-Home
2 code implementations • 21 Jul 2022 • Haotian Bai, Ruimao Zhang, Jiong Wang, Xiang Wan
Weakly Supervised Object Localization (WSOL), which aims to localize objects by only using image-level labels, has attracted much attention because of its low annotation cost in real applications.
Ranked #2 on Weakly-Supervised Object Localization on ImageNet
1 code implementation • 16 Jun 2022 • Yuanfeng Ji, Haotian Bai, Jie Yang, Chongjian Ge, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhang, Wanling Ma, Xiang Wan, Ping Luo
Constraint by the high cost of collecting and labeling 3D medical data, most of the deep learning models to date are driven by datasets with a limited number of organs of interest or samples, which still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of various methods.
1 code implementation • 21 May 2022 • Hao Ai, Zidong Cao, Jinjing Zhu, Haotian Bai, Yucheng Chen, Lin Wang
Omnidirectional image (ODI) data is captured with a 360x180 field-of-view, which is much wider than the pinhole cameras and contains richer spatial information than the conventional planar images.