no code implementations • 7 Feb 2024 • Wanli Ma, Oktay Karakus, Paul L. Rosin
The proposed semi-supervised learning-based knowledge distillation (SSLKD) approach demonstrates a notable improvement in the performance of the student model, in the application of road segmentation, surpassing the effectiveness of traditional semi-supervised learning methods.
no code implementations • 22 Nov 2023 • Wanli Ma, Oktay Karakus, Paul L. Rosin
There is still a lack of lightweight and efficient perturbation methods to promote the diversity of features and the precision of pseudo labels during training.
no code implementations • 9 Nov 2023 • Haokun Zhu, Juang Ian Chong, Teng Hu, Ran Yi, Yu-Kun Lai, Paul L. Rosin
Vector graphics are widely used in graphical designs and have received more and more attention.
no code implementations • 17 May 2023 • Wanli Ma, Oktay Karakus, Paul L. Rosin
Especially in the application of land cover classification, pixel-level manual labelling in large-scale imagery is labour-intensive, time-consuming and expensive.
1 code implementation • CVPR 2023 • Ran Yi, Haoyuan Tian, Zhihao Gu, Yu-Kun Lai, Paul L. Rosin
To fill the gap in the field of artistic image aesthetics assessment (AIAA), we first introduce a large-scale AIAA dataset: Boldbrush Artistic Image Dataset (BAID), which consists of 60, 337 artistic images covering various art forms, with more than 360, 000 votes from online users.
no code implementations • 19 Sep 2022 • Yifan Wang, Lin Zhang, Ran Song, Paul L. Rosin, Yibin Li, Wei zhang
It fully utilizes the relationship between a target sample and its neighbors in the source domain to avoid the influence of domain misalignment.
no code implementations • 19 Jul 2022 • Yifan Wang, Lin Zhang, Ran Song, Hongliang Li, Paul L. Rosin, Wei zhang
Specifically, we introduce a knowability-based labeling scheme which can be divided into two steps: 1) Knowability-guided detection of known and unknown samples based on the intrinsic structure of the neighborhoods of samples, where we leverage the first singular vectors of the affinity matrices to obtain the knowability of every target sample.
1 code implementation • 8 Feb 2022 • Ran Yi, Yong-Jin Liu, Yu-Kun Lai, Paul L. Rosin
In this paper, we propose a novel method to automatically transform face photos to portrait drawings using unpaired training data with two new features; i. e., our method can (1) learn to generate high quality portrait drawings in multiple styles using a single network and (2) generate portrait drawings in a "new style" unseen in the training data.
1 code implementation • CVPR 2021 • Ran Song, Wei zhang, Yitian Zhao, Yonghuai Liu, Paul L. Rosin
While mesh saliency aims to predict regional importance of 3D surfaces in agreement with human visual perception and is well researched in computer vision and graphics, latest work with eye-tracking experiments shows that state-of-the-art mesh saliency methods remain poor at predicting human fixations.
no code implementations • CVPR 2021 • Shao-Ping Lu, Rong Wang, Tao Zhong, Paul L. Rosin
Many attempts have been made to hide information in images, where the main challenge is how to increase the payload capacity without the container image being detected as containing a message.
no code implementations • 1 Sep 2020 • Paul L. Rosin, Yu-Kun Lai, David Mould, Ran Yi, Itamar Berger, Lars Doyle, Seungyong Lee, Chuan Li, Yong-Jin Liu, Amir Semmo, Ariel Shamir, Minjung Son, Holger Winnemoller
Despite the recent upsurge of activity in image-based non-photorealistic rendering (NPR), and in particular portrait image stylisation, due to the advent of neural style transfer, the state of performance evaluation in this field is limited, especially compared to the norms in the computer vision and machine learning communities.
1 code implementation • 12 Aug 2020 • Paul L. Rosin, Yu-Kun Lai
This paper describes a simple image-based method that applies engraving stylisation to portraits using ordered dithering.
no code implementations • 1 Mar 2020 • David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, A Bronstein, M Bronstein, S Bu, Umberto Castellani, S Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, L Lai, Bo Li, C. Li, Haisheng Li, Roee Litman, X. Liu, Z Liu, Yijuan Lu, L. Sun, G Tam, Atsushi Tatsuma, J. Ye
In addition, further participants have also taken part, and we provide extra analysis of the retrieval results.
no code implementations • 30 Oct 2019 • Yi-Ling Qiao, Lin Gao, Jie Yang, Paul L. Rosin, Yu-Kun Lai, Xilin Chen
3D models are commonly used in computer vision and graphics.
1 code implementation • ICCV 2019 • Deng-Ping Fan, Shengchuan Zhang, Yu-Huan Wu, Yun Liu, Ming-Ming Cheng, Bo Ren, Paul L. Rosin, Rongrong Ji
In this paper, we design a perceptual metric, called Structure Co-Occurrence Texture (Scoot), which simultaneously considers the block-level spatial structure and co-occurrence texture statistics.
no code implementations • 23 Jan 2019 • Jie Liang, Jufeng Yang, Ming-Ming Cheng, Paul L. Rosin, Liang Wang
In this paper we propose a unified framework to simultaneously discover the number of clusters and group the data points into them using subspace clustering.
1 code implementation • CVPR 2018 • Jufeng Yang, Dongyu She, Yu-Kun Lai, Paul L. Rosin, Ming-Hsuan Yang
The second branch utilizes both the holistic and localized information by coupling the sentiment map with deep features for robust classification.
no code implementations • CVPR 2018 • Jufeng Yang, Xiaoxiao Sun, Jie Liang, Paul L. Rosin
Accordingly, we design six medical representations considering different criteria for the recognition of skin lesions, and construct a diagnosis system for clinical skin disease images.
1 code implementation • 9 Apr 2018 • Deng-Ping Fan, Shengchuan Zhang, Yu-Huan Wu, Ming-Ming Cheng, Bo Ren, Rongrong Ji, Paul L. Rosin
However, human perception of the similarity of two sketches will consider both structure and texture as essential factors and is not sensitive to slight ("pixel-level") mismatches.
6 code implementations • CVPR 2019 • Song-Hai Zhang, Rui-Long Li, Xin Dong, Paul L. Rosin, Zixi Cai, Han Xi, Dingcheng Yang, Hao-Zhi Huang, Shi-Min Hu
We demonstrate that our pose-based framework can achieve better accuracy than the state-of-art detection-based approach on the human instance segmentation problem, and can moreover better handle occlusion.
Ranked #1 on Human Instance Segmentation on OCHuman
1 code implementation • 31 Aug 2017 • Huihuang Zhao, Paul L. Rosin, Yu-Kun Lai
This paper presents an automatic image synthesis method to transfer the style of an example image to a content image.
no code implementations • 6 Dec 2016 • Jia-Xing Zhao, Ren Bo, Qibin Hou, Ming-Ming Cheng, Paul L. Rosin
It also has drawbacks on convergence rate as a result of both the fixed search region and separately doing the assignment step and the update step.
no code implementations • 17 May 2016 • Kaelon Lloyd, David Marshall, Simon C. Moore, Paul L. Rosin
We utilise computer vision techniques to develop an automated method of abnormal crowd detection that can aid a human operator in the detection of violent behaviour.