Search Results for author: Rui Gong

Found 14 papers, 3 papers with code

Prompting Diffusion Representations for Cross-Domain Semantic Segmentation

no code implementations5 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.

Domain Generalization Image Generation +2

SF-FSDA: Source-Free Few-Shot Domain Adaptive Object Detection with Efficient Labeled Data Factory

no code implementations7 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.

object-detection Pseudo Label +1

Continuous Pseudo-Label Rectified Domain Adaptive Semantic Segmentation With Implicit Neural Representations

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.

Pseudo Label Semantic Segmentation +1

One-Shot Domain Adaptive and Generalizable Semantic Segmentation with Class-Aware Cross-Domain Transformers

no code implementations14 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.

Autonomous Driving Domain Adaptation +1

GGViT:Multistream Vision Transformer Network in Face2Face Facial Reenactment Detection

no code implementations12 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.

TACS: Taxonomy Adaptive Cross-Domain Semantic Segmentation

1 code implementation10 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.

Contrastive Learning Domain Adaptation +1

Self-Supervised Pretraining and Controlled Augmentation Improve Rare Wildlife Recognition in UAV Images

1 code implementation17 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.

Contrastive Learning

A Plant Root System Algorithm Based on Swarm Intelligence for One-dimensional Biomedical Signal Feature Engineering

no code implementations31 Jul 2021 Rui Gong, Kazunori Hase

To date, very few biomedical signals have transitioned from research applications to clinical applications.

Feature Engineering

Cluster, Split, Fuse, and Update: Meta-Learning for Open Compound Domain Adaptive Semantic Segmentation

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.

Domain Adaptation Meta-Learning +2

Self-Calibration Supported Robust Projective Structure-from-Motion

no code implementations4 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.

Camera Calibration valid

Analogical Image Translation for Fog Generation

no code implementations28 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.

Image-to-Image Translation Scene Understanding +1

DLOW: Domain Flow for Adaptation and Generalization

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.

Domain Adaptation Semantic Segmentation +1

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