English
Related papers

Related papers: Seeing Behind Dynamic Occlusions with Event Camera…

200 papers

Occlusions are very common in face images in the wild, leading to the degraded performance of face-related tasks. Although much effort has been devoted to removing occlusions from face images, the varying shapes and textures of occlusions…

Computer Vision and Pattern Recognition · Computer Science 2021-12-16 Xiangnan Yin , Di Huang , Zehua Fu , Yunhong Wang , Liming Chen

Event cameras are novel bio-inspired sensors that measure per-pixel brightness differences asynchronously. Recovering brightness from events is appealing since the reconstructed images inherit the high dynamic range (HDR) and high-speed…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Zelin Zhang , Anthony Yezzi , Guillermo Gallego

Event cameras offering high dynamic range and low latency have emerged as disruptive technologies in imaging. Despite growing research on leveraging these benefits for different imaging tasks, a comprehensive study of recently advances and…

Computer Vision and Pattern Recognition · Computer Science 2025-05-12 Yunfan Lu , Xiaogang Xu , Pengteng Li , Yusheng Wang , Yi Cui , Huizai Yao , Hui Xiong

This paper presents a novel method for detecting scene changes from a pair of images with a difference of camera viewpoints using a dense optical flow based change detection network. In the case that camera poses of input images are fixed…

Computer Vision and Pattern Recognition · Computer Science 2017-12-11 Ken Sakurada , Weimin Wang , Nobuo Kawaguchi , Ryosuke Nakamura

State-of-the-art video deblurring methods cannot handle blurry videos recorded in dynamic scenes, since they are built under a strong assumption that the captured scenes are static. Contrary to the existing methods, we propose a video…

Computer Vision and Pattern Recognition · Computer Science 2016-03-15 Tae Hyun Kim , Seungjun Nah , Kyoung Mu Lee

The ability to record high-fidelity videos at high acquisition rates is central to the study of fast moving phenomena. The difficulty of imaging fast moving scenes lies in a trade-off between motion blur and underexposure noise: On the one…

Computer Vision and Pattern Recognition · Computer Science 2022-11-30 Weihao Zhuang , Tristan Hascoet , Ryoichi Takashima , Tetsuya Takiguchi

With the popularity of monocular videos generated by video sharing and live broadcasting applications, reconstructing and editing dynamic scenes in stationary monocular cameras has become a special but anticipated technology. In contrast to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-02 Weixing Xie , Xiao Dong , Yong Yang , Qiqin Lin , Jingze Chen , Junfeng Yao , Xiaohu Guo

Existing video deraining methods are often trained on paired datasets, either synthetic, which limits their ability to generalize to real-world rain, or captured by static cameras, which restricts their effectiveness in dynamic scenes with…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Tuomas Varanka , Juan Luis Gonzalez , Hyeongwoo Kim , Pablo Garrido , Xu Yao

Traditional frame-based cameras inevitably suffer from motion blur due to long exposure times. As a kind of bio-inspired camera, the event camera records the intensity changes in an asynchronous way with high temporal resolution, providing…

Computer Vision and Pattern Recognition · Computer Science 2023-01-13 Lei Sun , Christos Sakaridis , Jingyun Liang , Qi Jiang , Kailun Yang , Peng Sun , Yaozu Ye , Kaiwei Wang , Luc Van Gool

Event cameras are sensors inspired by biological systems that specialize in capturing changes in brightness. These emerging cameras offer many advantages over conventional frame-based cameras, including high dynamic range, high frame rates,…

Computer Vision and Pattern Recognition · Computer Science 2023-09-04 Haodong Chen , Vera Chung , Li Tan , Xiaoming Chen

Event cameras are a paradigm shift in camera technology. Instead of full frames, the sensor captures a sparse set of events caused by intensity changes. Since only the changes are transferred, those cameras are able to capture quick…

Computer Vision and Pattern Recognition · Computer Science 2017-03-22 Christian Reinbacher , Gottfried Munda , Thomas Pock

Accurate and fast extraction of foreground object is a key prerequisite for a wide range of computer vision applications such as object tracking and recognition. Thus, enormous background subtraction methods for foreground object detection…

Computer Vision and Pattern Recognition · Computer Science 2019-05-01 Dongdong Zeng , Ming Zhu , Arjan Kuijper

Previous surface reconstruction methods either suffer from low geometric accuracy or lengthy training times when dealing with real-world complex dynamic scenes involving multi-person activities, and human-object interactions. To tackle the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-30 Shuo Wang , Binbin Huang , Ruoyu Wang , Shenghua Gao

We propose a method for converting a single RGB-D input image into a 3D photo - a multi-layer representation for novel view synthesis that contains hallucinated color and depth structures in regions occluded in the original view. We use a…

Computer Vision and Pattern Recognition · Computer Science 2020-06-11 Meng-Li Shih , Shih-Yang Su , Johannes Kopf , Jia-Bin Huang

Existing scene understanding systems mainly focus on recognizing the visible parts of a scene, ignoring the intact appearance of physical objects in the real-world. Concurrently, image completion has aimed to create plausible appearance for…

Computer Vision and Pattern Recognition · Computer Science 2021-04-13 Chuanxia Zheng , Duy-Son Dao , Guoxian Song , Tat-Jen Cham , Jianfei Cai

Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low-frequency reference intensity information. These…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Cedric Scheerlinck , Nick Barnes , Robert Mahony

Detection of moving objects in videos is a crucial step towards successful surveillance and monitoring applications. A key component for such tasks is called background subtraction and tries to extract regions of interest from the image…

Computer Vision and Pattern Recognition · Computer Science 2017-10-30 Konstantinos Makantasis , Antonis Nikitakis , Anastasios Doulamis , Nikolaos Doulamis , Yannis Papaefstathiou

Event cameras have gained increasing attention for 3D reconstruction due to their high temporal resolution, low latency, and high dynamic range. They capture per-pixel brightness changes asynchronously, allowing accurate reconstruction…

Graphics · Computer Science 2025-06-03 Chuanzhi Xu , Haoxian Zhou , Haodong Chen , Vera Chung , Qiang Qu

The diffusion of drones presents significant security and safety challenges. Traditional surveillance systems, particularly conventional frame-based cameras, struggle to reliably detect these targets due to their small size, high agility,…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Gabriele Magrini , Lorenzo Berlincioni , Luca Cultrera , Federico Becattini , Pietro Pala

Background objects occluded in some views of a light field (LF) camera can be seen by other views. Consequently, occluded surfaces are possible to be reconstructed from LF images. In this paper, we handle the LF de-occlusion (LF-DeOcc)…

Computer Vision and Pattern Recognition · Computer Science 2019-12-11 Yingqian Wang , Tianhao Wu , Jungang Yang , Longguang Wang , Wei An , Yulan Guo
‹ Prev 1 3 4 5 6 7 10 Next ›