no code implementations • 21 Mar 2024 • Zijie Wu, Mingtao Feng, Yaonan Wang, He Xie, Weisheng Dong, Bo Miao, Ajmal Mian
Generating realistic 3D scenes is challenging due to the complexity of room layouts and object geometries. We propose a sketch based knowledge enhanced diffusion architecture (SEK) for generating customized, diverse, and plausible 3D scenes.
no code implementations • 21 Mar 2024 • Haoran Hou, Mingtao Feng, Zijie Wu, Weisheng Dong, Qing Zhu, Yaonan Wang, Ajmal Mian
In this work, we focus on the distributional properties of point clouds and formulate the voting process as generating new points in the high-density region of the distribution of object centers.
no code implementations • 20 Mar 2024 • Qitong Yang, Mingtao Feng, Zijie Wu, ShiJie Sun, Weisheng Dong, Yaonan Wang, Ajmal Mian
To address this, we propose a novel framework that generates coherent 4D sequences with animation of 3D shapes under given conditions with dynamic evolution of shape and color over time through integrative latent mapping.
1 code implementation • 19 Mar 2024 • Jingtao Sun, Yaonan Wang, Mingtao Feng, Chao Ding, Mike Zheng Shou, Ajmal Saeed Mian
Furthermore, we introduce a pretrain-to-refine self-supervised training paradigm to train our network.
no code implementations • ICCV 2023 • Zijie Wu, Yaonan Wang, Mingtao Feng, He Xie, Ajmal Mian
In this paper, we propose a sketch and text guided probabilistic diffusion model for colored point cloud generation that conditions the denoising process jointly with a hand drawn sketch of the object and its textual description.
no code implementations • 8 Mar 2023 • Yong He, Hongshan Yu, Zhengeng Yang, Wei Sun, Mingtao Feng, Ajmal Mian
Local features and contextual dependencies are crucial for 3D point cloud analysis.
no code implementations • CVPR 2023 • Mingtao Feng, Haoran Hou, Liang Zhang, Zijie Wu, Yulan Guo, Ajmal Mian
In-depth understanding of a 3D scene not only involves locating/recognizing individual objects, but also requires to infer the relationships and interactions among them.
1 code implementation • 28 Apr 2022 • Mingtao Feng, Kendong Liu, Liang Zhang, Hongshan Yu, Yaonan Wang, Ajmal Mian
Saliency detection with light field images is becoming attractive given the abundant cues available, however, this comes at the expense of large-scale pixel level annotated data which is expensive to generate.
no code implementations • 3 Jan 2022 • Guangming Zhu, Liang Zhang, Youliang Jiang, Yixuan Dang, Haoran Hou, Peiyi Shen, Mingtao Feng, Xia Zhao, Qiguang Miao, Syed Afaq Ali Shah, Mohammed Bennamoun
In this paper, we provide a comprehensive survey of recent achievements in this field brought about by deep learning techniques.
1 code implementation • CVPR 2022 • Mingtao Feng, Kendong Liu, Liang Zhang, Hongshan Yu, Yaonan Wang, Ajmal Mian
Saliency detection with light field images is becoming attractive given the abundant cues available, however, this comes at the expense of large-scale pixel level annotated data which is expensive to generate.
1 code implementation • 24 Jun 2021 • Johann Li, Guangming Zhu, Cong Hua, Mingtao Feng, BasheerBennamoun, Ping Li, Xiaoyuan Lu, Juan Song, Peiyi Shen, Xu Xu, Lin Mei, Liang Zhang, Syed Afaq Ali Shah, Mohammed Bennamoun
Thus, as comprehensive as possible, this paper provides a collection of medical image datasets with their associated challenges for deep learning research.
1 code implementation • ICCV 2021 • Mingtao Feng, Zhen Li, Qi Li, Liang Zhang, Xiangdong Zhang, Guangming Zhu, HUI ZHANG, Yaonan Wang, Ajmal Mian
There are three main challenges in 3D object grounding: to find the main focus in the complex and diverse description; to understand the point cloud scene; and to locate the target object.
no code implementations • 11 Jun 2020 • Zijie Wu, Yaonan Wang, Qing Zhu, Jianxu Mao, Haotian Wu, Mingtao Feng, Ajmal Mian
Different from the most existing point set registration methods which usually extract the descriptors to find correspondences between point sets, our proposed MPE alignment method is able to handle large scale raw data offset without depending on traditional descriptors extraction, whether for the local or global registration methods.
no code implementations • 30 Nov 2019 • Mingtao Feng, Syed Zulqarnain Gilani, Yaonan Wang, Liang Zhang, Ajmal Mian
Convolutional Neural Networks (CNNs) have emerged as a powerful strategy for most object detection tasks on 2D images.
no code implementations • 27 Sep 2019 • Mingtao Feng, Liang Zhang, Xuefei Lin, Syed Zulqarnain Gilani, Ajmal Mian
We propose a point attention network that learns rich local shape features and their contextual correlations for 3D point cloud semantic segmentation.
no code implementations • 26 Apr 2018 • Xiang Yan, Syed Zulqarnain Gilani, Hanlin Qin, Mingtao Feng, Liang Zhang, Ajmal Mian
Detecting representative frames in videos based on human actions is quite challenging because of the combined factors of human pose in action and the background.
no code implementations • ECCV 2018 • Mingtao Feng, Syed Zulqarnain Gilani, Yaonan Wang, Ajmal Mian
Reconstructing 3D facial geometry from a single RGB image has recently instigated wide research interest.