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Fully-automatic execution is the ultimate goal for many Computer Vision applications. However, this objective is not always realistic in tasks associated with high failure costs, such as medical applications. For these tasks, semi-automatic…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Jing Yu Koh , Duc Thanh Nguyen , Quang-Trung Truong , Sai-Kit Yeung , Alexander Binder

Image fusion is famous as an alternative solution to generate one high-quality image from multiple images in addition to image restoration from a single degraded image. The essence of image fusion is to integrate complementary information…

Computer Vision and Pattern Recognition · Computer Science 2024-10-17 Pengwei Liang , Junjun Jiang , Qing Ma , Xianming Liu , Jiayi Ma

Edge detection is a classic problem in the field of image processing, which lays foundations for other tasks such as image segmentation. Conventionally, this operation is performed using gradient operators such as the Roberts or Sobel…

Computer Vision and Pattern Recognition · Computer Science 2017-01-16 Yuan-Hang Zhang , Xie Li , Jing-Yun Xiao

In this paper a novel approach for de noising images corrupted by random valued impulses has been proposed. Noise suppression is done in two steps. The detection of noisy pixels is done using all neighbor directional weighted pixels (ANDWP)…

Computer Vision and Pattern Recognition · Computer Science 2012-06-04 J. K. Mandal , Somnath Mukhopadhyay

Glass largely blurs the boundary between the real world and the reflection. The special transmittance and reflectance quality have confused the semantic tasks related to machine vision. Therefore, how to clear the boundary built by glass,…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Xiaolin Qin , Jiacen Liu , Qianlei Wang , Shaolin Zhang , Fei Zhu , Zhang Yi

Also recently, exciting strides forward have been made in the area of image restoration, particularly for image denoising and single image super-resolution. Deep learning techniques contributed to this significantly. The top methods differ…

Computer Vision and Pattern Recognition · Computer Science 2016-07-27 Jiqing Wu , Radu Timofte , Luc Van Gool

Existing position based point cloud filtering methods can hardly preserve sharp geometric features. In this paper, we rethink point cloud filtering from a non-learning non-local non-normal perspective, and propose a novel position based…

Computer Vision and Pattern Recognition · Computer Science 2021-10-15 Jinxi Wang , Jincen Jiang , Xuequan Lu , Meili Wang

Machine learning applied to computer vision and signal processing is achieving results comparable to the human brain on specific tasks due to the great improvements brought by the deep neural networks (DNN). The majority of state-of-the-art…

Computer Vision and Pattern Recognition · Computer Science 2020-06-30 José Augusto Stuchi , Levy Boccato , Romis Attux

The process of using one image to guide the filtering process of another one is called Guided Image Filtering (GIF). The main challenge of GIF is the structure inconsistency between the guidance image and the target image. Besides, noise in…

Computer Vision and Pattern Recognition · Computer Science 2017-03-29 Wei Liu , Xiaogang Chen , Chunhua Shen , Jingyi Yu , Qiang Wu , Jie Yang

In this paper, we tackle the problem of video alignment, the process of matching the frames of a pair of videos containing similar actions. The main challenge in video alignment is that accurate correspondence should be established despite…

Computer Vision and Pattern Recognition · Computer Science 2024-09-09 Niloufar Fakhfour , Mohammad ShahverdiKondori , Sajjad Hashembeiki , Mohammadjavad Norouzi , Hoda Mohammadzade

Source-Free Object Detection (SFOD) aims to adapt a source-pretrained object detector to a target domain without access to source data. However, existing SFOD methods predominantly rely on internal knowledge from the source model, which…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Huizai Yao , Sicheng Zhao , Pengteng Li , Yi Cui , Shuo Lu , Weiyu Guo , Yunfan Lu , Yijie Xu , Hui Xiong

The optimal implementation of federated learning (FL) in practical edge computing systems has been an outstanding problem. In this paper, we propose an optimization-based quantized FL algorithm, which can appropriately fit a general edge…

Machine Learning · Computer Science 2023-11-21 Yangchen Li , Ying Cui , Vincent Lau

Beyond novel view synthesis, Neural Radiance Fields are useful for applications that interact with the real world. In this paper, we use them as an implicit map of a given scene and propose a camera relocalization algorithm tailored for…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Arthur Moreau , Nathan Piasco , Moussab Bennehar , Dzmitry Tsishkou , Bogdan Stanciulescu , Arnaud de La Fortelle

Segmentation of an object from a video is a challenging task in multimedia applications. Depending on the application, automatic or interactive methods are desired; however, regardless of the application type, efficient computation of video…

Computer Vision and Pattern Recognition · Computer Science 2014-10-28 Ozan Sener , Kemal Ugur , A. Aydin Alatan

Feature point detection and description is the backbone for various computer vision applications, such as Structure-from-Motion, visual SLAM, and visual place recognition. While learning-based methods have surpassed traditional handcrafted…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Ali Youssef , Francisco Vasconcelos

The problem of image restoration in cryo-EM entails correcting for the effects of the Contrast Transfer Function (CTF) and noise. Popular methods for image restoration include `phase flipping', which corrects only for the Fourier phases but…

Computer Vision and Pattern Recognition · Computer Science 2016-04-29 Tejal Bhamre , Teng Zhang , Amit Singer

Neural Radiance Fields (NeRF) have demonstrated exceptional capabilities in reconstructing complex scenes with high fidelity. However, NeRF's view dependency can only handle low-frequency reflections. It falls short when handling complex…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Chen Gao , Yipeng Wang , Changil Kim , Jia-Bin Huang , Johannes Kopf

State-of-the-art neural implicit surface representations have achieved impressive results in indoor scene reconstruction by incorporating monocular geometric priors as additional supervision. However, we have observed that multi-view…

Computer Vision and Pattern Recognition · Computer Science 2024-05-02 Ziyi Chen , Xiaolong Wu , Yu Zhang

In this paper, we study a new problem, Film Removal (FR), which attempts to remove the interference of wrinkled transparent films and reconstruct the original information under films for industrial recognition systems. We first physically…

Computer Vision and Pattern Recognition · Computer Science 2024-03-08 Jiaqi Tang , Ruizheng Wu , Xiaogang Xu , Sixing Hu , Ying-Cong Chen

Leveraging 3D semantics for direct 3D reconstruction has a great potential yet unleashed. For instance, by assuming that walls are vertical, and a floor is planar and horizontal, we can correct distorted room shapes and eliminate local…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Anna Sokolova , Anna Vorontsova , Bulat Gabdullin , Alexander Limonov
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