no code implementations • 5 Jul 2023 • Rui Gong, Martin Danelljan, Han Sun, Julio Delgado Mangas, Luc van Gool
Intrigued by this result, we set out to explore how well diffusion-pretrained representations generalize to new domains, a crucial ability for any representation.
no code implementations • 7 Jun 2023 • Han Sun, Rui Gong, Konrad Schindler, Luc van Gool
Domain adaptive object detection aims to leverage the knowledge learned from a labeled source domain to improve the performance on an unlabeled target domain.
no code implementations • CVPR 2023 • Rui Gong, Qin Wang, Martin Danelljan, Dengxin Dai, Luc van Gool
Unsupervised domain adaptation (UDA) for semantic segmentation aims at improving the model performance on the unlabeled target domain by leveraging a labeled source domain.
no code implementations • 14 Dec 2022 • Rui Gong, Qin Wang, Dengxin Dai, Luc van Gool
Thus, we aim to relieve this need on a large number of real data, and explore the one-shot unsupervised sim-to-real domain adaptation (OSUDA) and generalization (OSDG) problem, where only one real-world data sample is available.
no code implementations • 12 Oct 2022 • Haotian Wu, Peipei Wang, Xin Wang, Ji Xiang, Rui Gong
The compression of videos on social media has destroyed some pixel details that could be used to detect forgeries.
1 code implementation • 10 Sep 2021 • Rui Gong, Martin Danelljan, Dengxin Dai, Danda Pani Paudel, Ajad Chhatkuli, Fisher Yu, Luc van Gool
In many real-world settings, the target domain task requires a different taxonomy than the one imposed by the source domain.
1 code implementation • 17 Aug 2021 • Xiaochen Zheng, Benjamin Kellenberger, Rui Gong, Irena Hajnsek, Devis Tuia
In detail, we examine a combination of recent contrastive learning methodologies like Momentum Contrast (MoCo) and Cross-Level Instance-Group Discrimination (CLD) to condition our model on the aerial images without the requirement for labels.
no code implementations • 31 Jul 2021 • Rui Gong, Kazunori Hase
To date, very few biomedical signals have transitioned from research applications to clinical applications.
no code implementations • ICCV 2021 • Rui Gong, Dengxin Dai, Yuhua Chen, Wen Li, Luc van Gool
One challenge of object recognition is to generalize to new domains, to more classes and/or to new modalities.
no code implementations • CVPR 2021 • Rui Gong, Yuhua Chen, Danda Pani Paudel, Yawei Li, Ajad Chhatkuli, Wen Li, Dengxin Dai, Luc van Gool
Open compound domain adaptation (OCDA) is a domain adaptation setting, where target domain is modeled as a compound of multiple unknown homogeneous domains, which brings the advantage of improved generalization to unseen domains.
no code implementations • 4 Jul 2020 • Rui Gong, Danda Pani Paudel, Ajad Chhatkuli, Luc van Gool
In this paper, we propose a unified SfM method, in which the matching process is supported by self-calibration constraints.
no code implementations • 28 Jun 2020 • Rui Gong, Dengxin Dai, Yu-Hua Chen, Wen Li, Luc van Gool
AIT achieves this zero-shot image translation capability by coupling a supervised training scheme in the synthetic domain, a cycle consistency strategy in the real domain, an adversarial training scheme between the two domains, and a novel network design.
no code implementations • 2 Aug 2019 • Henrik Skibbe, Akiya Watakabe, Ken Nakae, Carlos Enrique Gutierrez, Hiromichi Tsukada, Junichi Hata, Takashi Kawase, Rui Gong, Alexander Woodward, Kenji Doya, Hideyuki Okano, Tetsuo Yamamori, Shin Ishii
Understanding the connectivity in the brain is an important prerequisite for understanding how the brain processes information.
1 code implementation • CVPR 2019 • Rui Gong, Wen Li, Yu-Hua Chen, Luc van Gool
In this work, we present a domain flow generation(DLOW) model to bridge two different domains by generating a continuous sequence of intermediate domains flowing from one domain to the other.