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We tackle a challenging task: multi-view and multi-modal event detection that detects events in a wide-range real environment by utilizing data from distributed cameras and microphones and their weak labels. In this task, distributed…

Audio and Speech Processing · Electrical Eng. & Systems 2022-02-21 Masahiro Yasuda , Yasunori Ohishi , Shoichiro Saito , Noboru Harada

We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low-latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Daniel Gehrig , Henri Rebecq , Guillermo Gallego , Davide Scaramuzza

Event-based cameras have shown great promise in a variety of situations where frame based cameras suffer, such as high speed motions and high dynamic range scenes. However, developing algorithms for event measurements requires a new class…

Computer Vision and Pattern Recognition · Computer Science 2018-08-14 Alex Zihao Zhu , Liangzhe Yuan , Kenneth Chaney , Kostas Daniilidis

Utilization of event-based cameras is expected to improve the visual quality of video frame interpolation solutions. We introduce a learning-based method to exploit moving region boundaries in a video sequence to increase the overall…

Image and Video Processing · Electrical Eng. & Systems 2023-03-06 Ahmet Akman , Onur Selim Kılıç , A. Aydın Alatan

Event-based cameras are bio-inspired sensors that capture brightness change of every pixel in an asynchronous manner. Compared with frame-based sensors, event cameras have microsecond-level latency and high dynamic range, hence showing…

Computer Vision and Pattern Recognition · Computer Science 2023-03-20 Dongsheng Wang , Xu Jia , Yang Zhang , Xinyu Zhang , Yaoyuan Wang , Ziyang Zhang , Dong Wang , Huchuan Lu

A robust and efficient anomaly detection technique is proposed, capable of dealing with crowded scenes where traditional tracking based approaches tend to fail. Initial foreground segmentation of the input frames confines the analysis to…

Computer Vision and Pattern Recognition · Computer Science 2013-04-04 Vikas Reddy , Conrad Sanderson , Brian C. Lovell

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

We propose a computational imaging method for time-efficient light-field acquisition that combines a coded aperture with an event-based camera. Different from the conventional coded-aperture imaging method, our method applies a sequence of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Shuji Habuchi , Keita Takahashi , Chihiro Tsutake , Toshiaki Fujii , Hajime Nagahara

3D surface reconstruction is essential across applications of virtual reality, robotics, and mobile scanning. However, RGB-based reconstruction often fails in low-texture, low-light, and low-albedo scenes. Handheld LiDARs, now common on…

Image and Video Processing · Electrical Eng. & Systems 2024-12-02 Nikhil Behari , Aaron Young , Siddharth Somasundaram , Tzofi Klinghoffer , Akshat Dave , Ramesh Raskar

We introduce a method for using event camera data in novel view synthesis via Gaussian Splatting. Event cameras offer exceptional temporal resolution and a high dynamic range. Leveraging these capabilities allows us to effectively address…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Toshiya Yura , Ashkan Mirzaei , Igor Gilitschenski

Event cameras excel at high-speed, low-power, and high-dynamic-range scene perception. However, as they fundamentally record only relative intensity changes rather than absolute intensity, the resulting data streams suffer from a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Gang Xu , Zhiyu Zhu , Junhui Hou

We present a new effective way for performance capture of deforming meshes with fine-scale time-varying surface detail from multi-view video. Our method builds up on coarse 4D surface reconstructions, as obtained with commonly used…

Computer Vision and Pattern Recognition · Computer Science 2016-02-08 Nadia Robertini , Edilson De Aguiar , Thomas Helten , Christian Theobalt

3D scene flow characterizes how the points at the current time flow to the next time in the 3D Euclidean space, which possesses the capacity to infer autonomously the non-rigid motion of all objects in the scene. The previous methods for…

Computer Vision and Pattern Recognition · Computer Science 2022-09-28 Chaokang Jiang , Guangming Wang , Yanzi Miao , Hesheng Wang

Existing shape estimation methods for deformable object manipulation suffer from the drawbacks of being off-line, model dependent, noise-sensitive or occlusion-sensitive, and thus are not appropriate for manipulation tasks requiring high…

Robotics · Computer Science 2018-09-27 Tao Han , Xuan Zhao , Peigen Sun , Jia Pan

Low-light image enhancement (LLIE) aims to improve the visibility of images captured in poorly lit environments. Prevalent event-based solutions primarily utilize events triggered by motion, i.e., ''motion events'' to strengthen only the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Lei Sun , Yuhan Bao , Jiajun Zhai , Jingyun Liang , Yulun Zhang , Kaiwei Wang , Danda Pani Paudel , Luc Van Gool

Event cameras are novel vision sensors that sample, in an asynchronous fashion, brightness increments with low latency and high temporal resolution. The resulting streams of events are of high value by themselves, especially for high speed…

Computer Vision and Pattern Recognition · Computer Science 2021-04-13 F. Paredes-Vallés , G. C. H. E. de Croon

Three-dimensional (3D) object reconstruction based on differentiable rendering (DR) is an active research topic in computer vision. DR-based methods minimize the difference between the rendered and target images by optimizing both the shape…

Computer Vision and Pattern Recognition · Computer Science 2022-11-23 Chunyu Li , Taisuke Hashimoto , Eiichi Matsumoto , Hiroharu Kato

We present a new approach to direct depth estimation for Spatial Augmented Reality (SAR) applications using event cameras. These dynamic vision sensors are a great fit to be paired with laser projectors for depth estimation in a structured…

Computer Vision and Pattern Recognition · Computer Science 2024-02-16 Wieland Morgenstern , Niklas Gard , Simon Baumann , Anna Hilsmann , Peter Eisert

The availability of high-speed 3D video sensors has greatly facilitated 3D shape acquisition of dynamic and deformable objects, but high frame rate 3D reconstruction is always degraded by spatial noise and temporal fluctuations. This paper…

Computer Vision and Pattern Recognition · Computer Science 2017-08-08 Jie Zhang , Christos Maniatis , Luis Horna , Robert B. Fisher

Event cameras differ from conventional RGB cameras in that they produce asynchronous data sequences. While RGB cameras capture every frame at a fixed rate, event cameras only capture changes in the scene, resulting in sparse and…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Dan Yang , Mehmet Yamac
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