1 code implementation • ECCV 2020 • Guolei Sun, Salman Khan, Wen Li, Hisham Cholakkal, Fahad Shahbaz Khan, Luc van Gool
This way, in an effort to fix localization errors, our loss provides an extra supervisory signal that helps the model to better discriminate between similar classes.
no code implementations • 17 May 2023 • Zongwei Wu, Jingjing Wang, Zhuyun Zhou, Zhaochong An, Qiuping Jiang, Cédric Demonceaux, Guolei Sun, Radu Timofte
In this paper, we propose a novel approach by mining the Cross-Modal Semantics to guide the fusion and decoding of multimodal features, with the aim of controlling the modal contribution based on relative entropy.
1 code implementation • CVPR 2023 • Guolei Sun, Zhaochong An, Yun Liu, Ce Liu, Christos Sakaridis, Deng-Ping Fan, Luc van Gool
We further advance the frontier of this field by systematically studying a new challenge named indiscernible object counting (IOC), the goal of which is to count objects that are blended with respect to their surroundings.
1 code implementation • 21 Jul 2022 • Guolei Sun, Yun Liu, Hao Tang, Ajad Chhatkuli, Le Zhang, Luc van Gool
The essence of video semantic segmentation (VSS) is how to leverage temporal information for prediction.
1 code implementation • CVPR 2022 • Guolei Sun, Yun Liu, Henghui Ding, Thomas Probst, Luc van Gool
To address this problem, we propose a Coarse-to-Fine Feature Mining (CFFM) technique to learn a unified presentation of static contexts and motional contexts.
9 code implementations • 23 Aug 2021 • Jingyun Liang, JieZhang Cao, Guolei Sun, Kai Zhang, Luc van Gool, Radu Timofte
In particular, the deep feature extraction module is composed of several residual Swin Transformer blocks (RSTB), each of which has several Swin Transformer layers together with a residual connection.
Ranked #2 on Color Image Denoising on urban100 sigma15
1 code implementation • ICCV 2021 • Jingyun Liang, Guolei Sun, Kai Zhang, Luc van Gool, Radu Timofte
Extensive experiments on synthetic and real images show that the proposed MANet not only performs favorably for both spatially variant and invariant kernel estimation, but also leads to state-of-the-art blind SR performance when combined with non-blind SR methods.
no code implementations • 4 Aug 2021 • Guolei Sun, Yun Liu, Jingyun Liang, Luc van Gool
Due to the fact that fully supervised semantic segmentation methods require sufficient fully-labeled data to work well and can not generalize to unseen classes, few-shot segmentation has attracted lots of research attention.
2 code implementations • 6 Jun 2021 • Yun Liu, Yu-Huan Wu, Guolei Sun, Le Zhang, Ajad Chhatkuli, Luc van Gool
This paper tackles the low-efficiency flaw of the vision transformer caused by the high computational/space complexity in Multi-Head Self-Attention (MHSA).
no code implementations • 23 May 2021 • Guolei Sun, Yun Liu, Thomas Probst, Danda Pani Paudel, Nikola Popovic, Luc van Gool
This indicates that global scene context is essential, despite the seemingly bottom-up nature of the problem.
no code implementations • ICCV 2021 • Guolei Sun, Thomas Probst, Danda Pani Paudel, Nikola Popovic, Menelaos Kanakis, Jagruti Patel, Dengxin Dai, Luc van Gool
Multiple tasks are performed by switching between them, performing one task at a time.
1 code implementation • CVPR 2021 • Nikola Popovic, Danda Pani Paudel, Thomas Probst, Guolei Sun, Luc van Gool
Learning to perform spatially distributed tasks is motivated by the frequent availability of only sparse labels across tasks, and the desire for a compact multi-tasking network.
no code implementations • 17 Oct 2020 • Yunchao Wei, Shuai Zheng, Ming-Ming Cheng, Hang Zhao, LiWei Wang, Errui Ding, Yi Yang, Antonio Torralba, Ting Liu, Guolei Sun, Wenguan Wang, Luc van Gool, Wonho Bae, Junhyug Noh, Jinhwan Seo, Gunhee Kim, Hao Zhao, Ming Lu, Anbang Yao, Yiwen Guo, Yurong Chen, Li Zhang, Chuangchuang Tan, Tao Ruan, Guanghua Gu, Shikui Wei, Yao Zhao, Mariia Dobko, Ostap Viniavskyi, Oles Dobosevych, Zhendong Wang, Zhenyuan Chen, Chen Gong, Huanqing Yan, Jun He
The purpose of the Learning from Imperfect Data (LID) workshop is to inspire and facilitate the research in developing novel approaches that would harness the imperfect data and improve the data-efficiency during training.
2 code implementations • ECCV 2020 • Guolei Sun, Wenguan Wang, Jifeng Dai, Luc van Gool
Moreover, our approach ranked 1st place in the Weakly-Supervised Semantic Segmentation Track of CVPR2020 Learning from Imperfect Data Challenge.
Object Localization Weakly supervised Semantic Segmentation +1
1 code implementation • 31 Mar 2020 • Hao Tang, Xiaojuan Qi, Guolei Sun, Dan Xu, Nicu Sebe, Radu Timofte, Luc van Gool
We propose a novel ECGAN for the challenging semantic image synthesis task.
no code implementations • 14 Dec 2019 • Guolei Sun, Hisham Cholakkal, Salman Khan, Fahad Shahbaz Khan, Ling Shao
The main requisite for fine-grained recognition task is to focus on subtle discriminative details that make the subordinate classes different from each other.
Ranked #14 on Fine-Grained Image Classification on Stanford Dogs
1 code implementation • 13 Dec 2019 • Hisham Cholakkal, Guolei Sun, Salman Khan, Fahad Shahbaz Khan, Ling Shao, Luc van Gool
Our RLC framework further reduces the annotation cost arising from large numbers of object categories in a dataset by only using lower-count supervision for a subset of categories and class-labels for the remaining ones.
Image Classification Image-level Supervised Instance Segmentation +2
3 code implementations • 30 May 2019 • Syed Waqas Zamir, Aditya Arora, Akshita Gupta, Salman Khan, Guolei Sun, Fahad Shahbaz Khan, Fan Zhu, Ling Shao, Gui-Song Xia, Xiang Bai
Compared to existing small-scale aerial image based instance segmentation datasets, iSAID contains 15$\times$ the number of object categories and 5$\times$ the number of instances.
Ranked #1 on Object Detection on iSAID
2 code implementations • CVPR 2019 • Hisham Cholakkal, Guolei Sun, Fahad Shahbaz Khan, Ling Shao
Moreover, our approach improves state-of-the-art image-level supervised instance segmentation with a relative gain of 17. 8% in terms of average best overlap, on the PASCAL VOC 2012 dataset.
Ranked #1 on Object Counting on COCO count-test
Image-level Supervised Instance Segmentation Object Counting +1
no code implementations • 18 Oct 2017 • Guolei Sun, Xiangliang Zhang
In this paper, we proposed a novel and general framework of representation learning for graph with rich text information through constructing a bipartite heterogeneous network.