no code implementations • 22 Apr 2024 • Yinzhe Xu, Huajian Huang, Yingshu Chen, Sai-Kit Yeung
Visual object tracking and segmentation in omnidirectional videos are challenging due to the wide field-of-view and large spherical distortion brought by 360{\deg} images.
no code implementations • 16 Apr 2024 • Yingshu Chen, Huajian Huang, Tuan-Anh Vu, Ka Chun Shum, Sai-Kit Yeung
We then optimize the scene style globally by adapting the scale of the style image with the scale of the training views.
no code implementations • 12 Apr 2024 • Hai Nguyen-Truong, E-Ro Nguyen, Tuan-Anh Vu, Minh-Triet Tran, Binh-Son Hua, Sai-Kit Yeung
Our method involves using CLIP to derive a CLIP Prior that integrates an object-centric visual heatmap with text description, which can be used as the initial query in DETR-based architecture for the segmentation task.
no code implementations • 4 Apr 2024 • Longwei Li, Huajian Huang, Sai-Kit Yeung, Hui Cheng
In this paper, we present OmniGS, a novel omnidirectional Gaussian splatting system, to take advantage of omnidirectional images for fast radiance field reconstruction.
no code implementations • 25 Jan 2024 • Quang-Trung Truong, Duc Thanh Nguyen, Binh-Son Hua, Sai-Kit Yeung
This is enabled by deformable attention mechanism, where the keys and values capturing the memory of a video sequence in the attention module have flexible locations updated across frames.
Ranked #9 on Unsupervised Video Object Segmentation on DAVIS 2016 val (using extra training data)
no code implementations • 4 Jan 2024 • Ziqiang Zheng, YiWei Chen, Jipeng Zhang, Tuan-Anh Vu, Huimin Zeng, Yue Him Wong Tim, Sai-Kit Yeung
In this study, we carry out the preliminary and comprehensive case study of utilizing GPT-4V for marine analysis.
no code implementations • 29 Dec 2023 • Tuan-Anh Vu, Duc Thanh Nguyen, Qing Guo, Binh-Son Hua, Nhat Minh Chung, Ivor W. Tsang, Sai-Kit Yeung
Such cross-domain representations are desirable in segmenting camouflaged objects where visual cues are subtle to distinguish the objects from the background, especially in segmenting novel objects which are not seen in training.
1 code implementation • 30 Nov 2023 • Yingshu Chen, Guocheng Shao, Ka Chun Shum, Binh-Son Hua, Sai-Kit Yeung
Building on such taxonomy, our survey first revisits the background of neural stylization on 2D images, and then provides in-depth discussions on recent neural stylization methods for 3D data, where we also provide a mini-benchmark on artistic stylization methods.
no code implementations • 29 Nov 2023 • Huajian Huang, Changkun Liu, Yipeng Zhu, Hui Cheng, Tristan Braud, Sai-Kit Yeung
We propose a virtual camera approach to generate lower-FoV query frames from 360$^\circ$ images, which ensures a fair comparison of performance among different query types in visual localization tasks.
1 code implementation • 28 Nov 2023 • Huajian Huang, Longwei Li, Hui Cheng, Sai-Kit Yeung
In addition to actively densifying hyper primitives based on geometric features, we further introduce a Gaussian-Pyramid-based training method to progressively learn multi-level features, enhancing photorealistic mapping performance.
no code implementations • 23 Nov 2023 • Benjamin Kiefer, Lojze Žust, Matej Kristan, Janez Perš, Matija Teršek, Arnold Wiliem, Martin Messmer, Cheng-Yen Yang, Hsiang-Wei Huang, Zhongyu Jiang, Heng-Cheng Kuo, Jie Mei, Jenq-Neng Hwang, Daniel Stadler, Lars Sommer, Kaer Huang, Aiguo Zheng, Weitu Chong, Kanokphan Lertniphonphan, Jun Xie, Feng Chen, Jian Li, Zhepeng Wang, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Tuan-Anh Vu, Hai Nguyen-Truong, Tan-Sang Ha, Quan-Dung Pham, Sai-Kit Yeung, Yuan Feng, Nguyen Thanh Thien, Lixin Tian, Sheng-Yao Kuan, Yuan-Hao Ho, Angel Bueno Rodriguez, Borja Carrillo-Perez, Alexander Klein, Antje Alex, Yannik Steiniger, Felix Sattler, Edgardo Solano-Carrillo, Matej Fabijanić, Magdalena Šumunec, Nadir Kapetanović, Andreas Michel, Wolfgang Gross, Martin Weinmann
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV).
Ranked #1 on Semantic Segmentation on LaRS
no code implementations • 22 Nov 2023 • Tuan-Anh Vu, Srinjay Sarkar, Zhiyuan Zhang, Binh-Son Hua, Sai-Kit Yeung
We are inspired by the recent revolution of learning implicit representation and point cloud upsampling, which can produce high-quality 3D surface reconstruction and proximity-to-surface, respectively.
1 code implementation • 20 Oct 2023 • Ziqiang Zheng, Jipeng Zhang, Tuan-Anh Vu, Shizhe Diao, Yue Him Wong Tim, Sai-Kit Yeung
Large language models (LLMs), such as ChatGPT/GPT-4, have proven to be powerful tools in promoting the user experience as an AI assistant.
no code implementations • 3 Oct 2023 • Liang Haixin, Zheng Ziqiang, Ma Zeyu, Sai-Kit Yeung
To achieve OMOD, we present \textbf{MarineDet}.
no code implementations • 3 Oct 2023 • Zheng Ziqiang, Xie Yaofeng, Liang Haixin, Yu Zhibin, Sai-Kit Yeung
We perform experiments on our CoralVOS dataset, including 6 recent state-of-the-art video object segmentation (VOS) algorithms.
1 code implementation • 20 Sep 2023 • Ka Chun Shum, Jaeyeon Kim, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung
Specifically, to insert a new foreground object represented by a set of multi-view images into a background radiance field, we use a text-to-image diffusion model to learn and generate combined images that fuse the object of interest into the given background across views.
1 code implementation • ICCV 2023 • Hong-Wing Pang, Binh-Son Hua, Sai-Kit Yeung
In this work, we propose a stylization framework for NeRF based on local style transfer.
1 code implementation • ICCV 2023 • Huajian Huang, Yinzhe Xu, Yingshu Chen, Sai-Kit Yeung
360{\deg} images can provide an omnidirectional field of view which is important for stable and long-term scene perception.
no code implementations • ICCV 2023 • Ka Chun Shum, Hong-Wing Pang, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung
We use this object layout to condition a generative adversarial network to synthesize images of an input scene.
no code implementations • 7 Jun 2023 • Tan-Sang Ha, Hai Nguyen-Truong, Tuan-Anh Vu, Sai-Kit Yeung
Building a video retrieval system that is robust and reliable, especially for the marine environment, is a challenging task due to several factors such as dealing with massive amounts of dense and repetitive data, occlusion, blurriness, low lighting conditions, and abstract queries.
no code implementations • 24 Nov 2022 • Benjamin Kiefer, Matej Kristan, Janez Perš, Lojze Žust, Fabio Poiesi, Fabio Augusto de Alcantara Andrade, Alexandre Bernardino, Matthew Dawkins, Jenni Raitoharju, Yitong Quan, Adem Atmaca, Timon Höfer, Qiming Zhang, Yufei Xu, Jing Zhang, DaCheng Tao, Lars Sommer, Raphael Spraul, Hangyue Zhao, Hongpu Zhang, Yanyun Zhao, Jan Lukas Augustin, Eui-ik Jeon, Impyeong Lee, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Sagar Verma, Siddharth Gupta, Shishir Muralidhara, Niharika Hegde, Daitao Xing, Nikolaos Evangeliou, Anthony Tzes, Vojtěch Bartl, Jakub Špaňhel, Adam Herout, Neelanjan Bhowmik, Toby P. Breckon, Shivanand Kundargi, Tejas Anvekar, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudengudi, Arpita Vats, Yang song, Delong Liu, Yonglin Li, Shuman Li, Chenhao Tan, Long Lan, Vladimir Somers, Christophe De Vleeschouwer, Alexandre Alahi, Hsiang-Wei Huang, Cheng-Yen Yang, Jenq-Neng Hwang, Pyong-Kun Kim, Kwangju Kim, Kyoungoh Lee, Shuai Jiang, Haiwen Li, Zheng Ziqiang, Tuan-Anh Vu, Hai Nguyen-Truong, Sai-Kit Yeung, Zhuang Jia, Sophia Yang, Chih-Chung Hsu, Xiu-Yu Hou, Yu-An Jhang, Simon Yang, Mau-Tsuen Yang
The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection.
no code implementations • 16 Nov 2022 • Jaeyeon Kim, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung
In this paper, we propose a new method for mapping a 3D point cloud to the latent space of a 3D generative adversarial network.
1 code implementation • 23 Sep 2022 • Quang-Trung Truong, Tuan-Anh Vu, Tan-Sang Ha, Lokoc Jakub, Yue Him Wong Tim, Ajay Joneja, Sai-Kit Yeung
It is important to remember that domain specific data may be noisier (e. g., endoscopic or underwater videos) and often require more experienced users for effective search.
Ranked #1 on Retrieval on MVK
1 code implementation • 13 Sep 2022 • Yingshu Chen, Tuan-Anh Vu, Ka-Chun Shum, Binh-Son Hua, Sai-Kit Yeung
Architectural photography is a genre of photography that focuses on capturing a building or structure in the foreground with dramatic lighting in the background.
no code implementations • 4 Aug 2022 • Huajian Huang, Yingshu Chen, Tianjia Zhang, Sai-Kit Yeung
Subsequently, we assign local radiance fields through an adaptive divide-and-conquer strategy based on the recovered geometry.
1 code implementation • 30 Mar 2022 • Tuan-Anh Vu, Duc Thanh Nguyen, Binh-Son Hua, Quang-Hieu Pham, Sai-Kit Yeung
The key insight is simultaneously performing both tasks via learning of spatial and temporal features from a sequence of point clouds can leverage individual tasks, leading to improved overall performance.
Ranked #1 on 3D Human Reconstruction on Dynamic FAUST
1 code implementation • 26 Feb 2022 • Zhiyuan Zhang, Binh-Son Hua, Sai-Kit Yeung
3D point clouds deep learning is a promising field of research that allows a neural network to learn features of point clouds directly, making it a robust tool for solving 3D scene understanding tasks.
no code implementations • 24 Nov 2021 • Hao Ren, Ziqiang Zheng, Yang Wu, Hong Lu, Yang Yang, Ying Shan, Sai-Kit Yeung
The huge domain gap between sketches and photos and the highly abstract sketch representations pose challenges for sketch-based image retrieval (\underline{SBIR}).
1 code implementation • 4 Aug 2021 • Hong-Wing Pang, Yingshu Chen, Phuoc-Hieu Le, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung
In this paper, we introduce a new problem of domain-specific indoor scene image synthesis, namely neural scene decoration.
no code implementations • 23 Sep 2020 • Huajian Huang, Wen-Yan Lin, Siying Liu, Dong Zhang, Sai-Kit Yeung
As local pose estimation is ill-conditioned, local pose estimation failures happen regularly, making the overall SLAM system brittle.
no code implementations • ICCV 2021 • Jaeyeon Kim, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung
With recent developments of convolutional neural networks, deep learning for 3D point clouds has shown significant progress in various 3D scene understanding tasks, e. g., object recognition, semantic segmentation.
no code implementations • 7 Aug 2020 • Zhiyuan Zhang, Binh-Son Hua, Wei Chen, Yibin Tian, Sai-Kit Yeung
We found that a key reason is that compared to point coordinates, rotation-invariant features consumed by point cloud convolution are not as distinctive.
no code implementations • ECCV 2020 • Jing Yu Koh, Duc Thanh Nguyen, Quang-Trung Truong, Sai-Kit Yeung, Alexander Binder
Fully-automatic execution is the ultimate goal for many Computer Vision applications.
1 code implementation • 21 Nov 2019 • Quang-Hieu Pham, Mikaela Angelina Uy, Binh-Son Hua, Duc Thanh Nguyen, Gemma Roig, Sai-Kit Yeung
In this work, we present a novel method to learn a local cross-domain descriptor for 2D image and 3D point cloud matching.
1 code implementation • ICCV 2019 • Zhiyuan Zhang, Binh-Son Hua, Sai-Kit Yeung
Deep learning with 3D data has progressed significantly since the introduction of convolutional neural networks that can handle point order ambiguity in point cloud data.
Ranked #8 on 3D Semantic Segmentation on DALES
1 code implementation • 17 Aug 2019 • Zhiyuan Zhang, Binh-Son Hua, David W. Rosen, Sai-Kit Yeung
Our core idea is to use low-level rotation invariant geometric features such as distances and angles to design a convolution operator for point cloud learning.
1 code implementation • ICCV 2019 • Mikaela Angelina Uy, Quang-Hieu Pham, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung
From our comprehensive benchmark, we show that our dataset poses great challenges to existing point cloud classification techniques as objects from real-world scans are often cluttered with background and/or are partial due to occlusions.
1 code implementation • CVPR 2019 • Quang-Hieu Pham, Duc Thanh Nguyen, Binh-Son Hua, Gemma Roig, Sai-Kit Yeung
Deep learning techniques have become the to-go models for most vision-related tasks on 2D images.
Ranked #2 on 3D Instance Segmentation on SceneNN
3D Instance Segmentation 3D Semantic Instance Segmentation +3
no code implementations • ECCV 2018 • Tian Feng, Quang-Trung Truong, Duc Thanh Nguyen, Jing Yu Koh, Lap-Fai Yu, Alexander Binder, Sai-Kit Yeung
Urban zoning enables various applications in land use analysis and urban planning.
no code implementations • CVPR 2018 • Daniel Teo, Boxin Shi, Yinqiang Zheng, Sai-Kit Yeung
We present a self-calibrating polarising radiometric calibration method.
no code implementations • CVPR 2018 • Zhipeng Mo, Boxin Shi, Feng Lu, Sai-Kit Yeung, Yasuyuki Matsushita
This paper presents a photometric stereo method that works with unknown natural illuminations without any calibration object.
no code implementations • 1 Apr 2018 • Quang-Hieu Pham, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung
The widespread adoption of autonomous systems such as drones and assistant robots has created a need for real-time high-quality semantic scene segmentation.
1 code implementation • CVPR 2018 • Binh-Son Hua, Minh-Khoi Tran, Sai-Kit Yeung
Deep learning with 3D data such as reconstructed point clouds and CAD models has received great research interests recently.
1 code implementation • CVPR 2017 • Jia-Wang Bian, Wen-Yan Lin, Yasuyuki Matsushita, Sai-Kit Yeung, Tan-Dat Nguyen, Ming-Ming Cheng
Incorporating smoothness constraints into feature matching is known to enable ultra-robust matching.
no code implementations • CVPR 2017 • Zhipeng Mo, Boxin Shi, Sai-Kit Yeung, Yasuyuki Matsushita
Radiometrically calibrating the images from Internet photo collections brings photometric analysis from lab data to big image data in the wild, but conventional calibration methods cannot be directly applied to such image data.
no code implementations • 19 Oct 2016 • Duc Thanh Nguyen, Binh-Son Hua, Lap-Fai Yu, Sai-Kit Yeung
Recent advances of 3D acquisition devices have enabled large-scale acquisition of 3D scene data.
no code implementations • CVPR 2016 • Boxin Shi, Zhe Wu, Zhipeng Mo, Dinglong Duan, Sai-Kit Yeung, Ping Tan
Recent progress on photometric stereo extends the technique to deal with general materials and unknown illumination conditions.
no code implementations • CVPR 2016 • Duc Thanh Nguyen, Binh-Son Hua, Khoi Tran, Quang-Hieu Pham, Sai-Kit Yeung
The proposed method was evaluated on both artificial data and real data obtained from reconstruction of practical scenes.
no code implementations • 12 Mar 2016 • Zhe Wu, Sai-Kit Yeung, Ping Tan
We present a portable device to capture both shape and reflectance of an indoor scene.
no code implementations • 16 Feb 2016 • Junyan Wang, Sai-Kit Yeung, Jue Wang, Kun Zhou
Comprehensive experiments on both RGB and RGB-D data demonstrate that our simple and effective method significantly outperforms the segmentation propagation methods adopted in the state-of-the-art video cutout systems, and the results also suggest the potential usefulness of our method in image cutout system.
no code implementations • 19 Jan 2016 • Tai-Pang Wu, Sai-Kit Yeung, Jiaya Jia, Chi-Keung Tang, Gerard Medioni
We prove a closed-form solution to tensor voting (CFTV): given a point set in any dimensions, our closed-form solution provides an exact, continuous and efficient algorithm for computing a structure-aware tensor that simultaneously achieves salient structure detection and outlier attenuation.
no code implementations • ICCV 2015 • Duc Thanh Nguyen, Minh-Khoi Tran, Sai-Kit Yeung
The problem of human detection is then formulated as maximum a posteriori (MAP) estimation in the MRF model.
no code implementations • ICCV 2015 • Lap-Fai Yu, Noah Duncan, Sai-Kit Yeung
We apply our approach to reason about the containability of several real-world objects acquired using a consumer-grade depth camera.
no code implementations • 23 Mar 2015 • Junyan Wang, Sai-Kit Yeung
Superpixels have become prevalent in computer vision.
no code implementations • 9 Apr 2014 • Junyan Wang, Sai-Kit Yeung
We propose a novel compact linear programming (LP) relaxation for binary sub-modular MRF in the context of object segmentation.
no code implementations • CVPR 2013 • Lap-Fai Yu, Sai-Kit Yeung, Yu-Wing Tai, Stephen Lin
We present a shading-based shape refinement algorithm which uses a noisy, incomplete depth map from Kinect to help resolve ambiguities in shape-from-shading.