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Event-based cameras record an asynchronous stream of per-pixel brightness changes. As such, they have numerous advantages over the standard frame-based cameras, including high temporal resolution, high dynamic range, and no motion blur. Due…

Computer Vision and Pattern Recognition · Computer Science 2020-10-01 Dimche Kostadinov , Davide Scaramuzza

The occlusion issues of computer vision (CV) applications in construction have attracted significant attention, especially those caused by the wide-coverage, crisscrossed, and immovable scaffold. Intuitively, removing the scaffold and…

Computer Vision and Pattern Recognition · Computer Science 2023-07-26 Yuexiong Ding , Muyang Liu , Xiaowei Luo

Event cameras or neuromorphic cameras mimic the human perception system as they measure the per-pixel intensity change rather than the actual intensity level. In contrast to traditional cameras, such cameras capture new information about…

Computer Vision and Pattern Recognition · Computer Science 2016-08-05 Christian Reinbacher , Gottfried Graber , Thomas Pock

Capturing and reconstructing high-speed dynamic 3D scenes has numerous applications in computer graphics, vision, and interdisciplinary fields such as robotics, aerodynamics, and evolutionary biology. However, achieving this using a single…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Zihao Zou , Ziyuan Qu , Xi Peng , Vivek Boominathan , Adithya Pediredla , Praneeth Chakravarthula

Visual reconstruction of fast non-rigid object deformations over time is a challenge for conventional frame-based cameras. In this paper, we propose a novel approach for reconstructing such deformations using measurements from event-based…

Computer Vision and Pattern Recognition · Computer Science 2022-11-15 Yuxuan Xue , Haolong Li , Stefan Leutenegger , Jörg Stückler

Event cameras are novel sensors that output brightness changes in the form of a stream of asynchronous events instead of intensity frames. Compared to conventional image sensors, they offer significant advantages: high temporal resolution,…

Computer Vision and Pattern Recognition · Computer Science 2020-10-23 Javier Hidalgo-Carrió , Daniel Gehrig , Davide Scaramuzza

Reconstructing static 3D scene from monocular video with dynamic objects is important for numerous applications such as virtual reality and autonomous driving. Current approaches typically rely on background for static scene reconstruction,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Yedong Shen , Shiqi Zhang , Sha Zhang , Yifan Duan , Xinran Zhang , Wenhao Yu , Lu Zhang , Jiajun Deng , Yanyong Zhang

Human activities are inherently complex, often involving numerous object interactions. To better understand these activities, it is crucial to model their interactions with the environment captured through dynamic changes. The recent…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Daiwei Zhang , Gengyan Li , Jiajie Li , Mickaël Bressieux , Otmar Hilliges , Marc Pollefeys , Luc Van Gool , Xi Wang

Current methods for 2D and 3D object understanding struggle with severe occlusions in busy urban environments, partly due to the lack of large-scale labeled ground-truth annotations for learning occlusion. In this work, we introduce a novel…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Khiem Vuong , N. Dinesh Reddy , Robert Tamburo , Srinivasa G. Narasimhan

In dynamic scenes, images often suffer from dynamic blur due to superposition of motions or low signal-noise ratio resulted from quick shutter speed when avoiding motions. Recovering sharp and clean results from the captured images heavily…

Computer Vision and Pattern Recognition · Computer Science 2022-03-24 Cheng Zhang , Shaolin Su , Yu Zhu , Qingsen Yan , Jinqiu Sun , Yanning Zhang

Single-view 3D shape retrieval is a challenging task that is increasingly important with the growth of available 3D data. Prior work that has studied this task has not focused on evaluating how realistic occlusions impact performance, and…

Computer Vision and Pattern Recognition · Computer Science 2024-01-02 Qirui Wu , Daniel Ritchie , Manolis Savva , Angel X. Chang

Unlike traditional cameras which synchronously register pixel intensity, neuromorphic sensors only register `changes' at pixels where a change is occurring asynchronously. This enables neuromorphic sensors to sample at a micro-second level…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Harbir Antil , Daniel Blauvelt , David Sayre

We present the first purely event-based method for face detection using the high temporal resolution of an event-based camera. We will rely on a new feature that has never been used for such a task that relies on detecting eye blinks. Eye…

Computer Vision and Pattern Recognition · Computer Science 2022-05-16 Gregor Lenz , Sio-Hoi Ieng , Ryad Benosman

Scene background initialization allows the recovery of a clear image without foreground objects from a video sequence, which is generally the first step in many computer vision and video processing applications. The process may be strongly…

Computer Vision and Pattern Recognition · Computer Science 2018-05-18 Zhe Xu , Biao Min , Ray C. C. Cheung

We introduce a novel framework for reconstructing dynamic human-object interactions from monocular video that overcomes challenges associated with occlusions and temporal inconsistencies. Traditional 3D reconstruction methods typically…

Computer Vision and Pattern Recognition · Computer Science 2025-09-16 Hyungjun Doh , Dong In Lee , Seunggeun Chi , Pin-Hao Huang , Kwonjoon Lee , Sangpil Kim , Karthik Ramani

Although deep-learning based methods for monocular pedestrian detection have made great progress, they are still vulnerable to heavy occlusions. Using multi-view information fusion is a potential solution but has limited applications, due…

Computer Vision and Pattern Recognition · Computer Science 2022-07-26 Rui Qiu , Ming Xu , Yuyao Yan , Jeremy S. Smith , Xi Yang

Camera anomalies like rain or dust can severelydegrade image quality and its related tasks, such as localizationand segmentation. In this work we address this importantissue by implementing a pre-processing step that can effectivelymitigate…

Computer Vision and Pattern Recognition · Computer Science 2021-09-07 Gianmario Fumagalli , Yannick Huber , Marcin Dymczyk , Roland Siegwart , Renaud Dubé

We seek to answer the question: what can a motion-blurred image reveal about a scene's past, present, and future? Although motion blur obscures image details and degrades visual quality, it also encodes information about scene and camera…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 SaiKiran Tedla , Kelly Zhu , Trevor Canham , Felix Taubner , Michael S. Brown , Kiriakos N. Kutulakos , David B. Lindell

For visual estimation of optical flow, a crucial function for many vision tasks, unsupervised learning, using the supervision of view synthesis has emerged as a promising alternative to supervised methods, since ground-truth flow is not…

Computer Vision and Pattern Recognition · Computer Science 2023-04-17 Zitang Sun , Shin'ya Nishida , Zhengbo Luo

3D object detection is essential for autonomous systems, enabling precise localization and dimension estimation. While LiDAR and RGB cameras are widely used, their fixed frame rates create perception gaps in high-speed scenarios. Event…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Jae-Young Kang , Hoonhee Cho , Kuk-Jin Yoon